Software Engineer jobs in United States, New York

CNS - BC - FINANCE :

It has multiple fields of play such as:

Supply Chain and Operations - we provide a unique combination of industry-specific, strategic, operational and financial insights, digital technology advances and strategic alliance partners to deliver better outcomes and also help clients effect fundamental change in their operations’ performance to support sales growth, become more cost competitive, minimize risk and ensure operational resilience.

Technical Excellence

• Demonstrated proficiency in financial analysis and modeling to support strategic decision-making. Strong understanding of industry trends and best practices in business consulting, particularly within the finance sector. Proven ability to develop actionable insights through market research and competitive analysis. Experience in designing and implementing business strategies that drive operational efficiencies for clients. Capable of utilizing consulting frameworks and methodologies to deliver effective solutions tailored to client needs.

Qualification

• Master of Business Administration

Experience

• Project Management (6+ years)

People with the ability to work in a collaborative manner to provide services across multiple client departments while following the commercial and legal requirements. You will need a practical approach to solving issues and complex problems with the ability to deliver insightful and practical solutions. We look for people who are agile, curious, mindful, and able to sustain positive energy, while being adaptable and creative in their approach.If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.

The opportunity

• Leads the delivery of solution or infrastructure development services for a large or more complex project, using strong technical capabilities and outstanding hands-on experience!
• Takes accountability for the design, development, delivery and maintenance of solutions or infrastructure, driving compliance with and contributing to the development of relevant standards
• Fully understands business and user requirements and ensures design specifications meet the requirements from a business and technical perspective

Your key responsibilities

• Solves complex and escalated aspects of a project, performing coding, debugging, testing and troubleshooting throughout the development process
• Provides advanced technical expertise to maximize efficiency, reliability and value from current solutions, infrastructure and emerging technologies, showing technical leadership and identifying and implementing continuous improvement plans
• Develops strong working relationships with peers across Development & Engineering and Architecture teams, collaborating to develop and engineer leading solutions
• Provides a leadership role for the work group, ensuring the appropriate expectations, principles, structures, tools and responsibilities are in place to deliver the project
• Drives consistency to the relevant processes, procedures, standards, technical design whilst supporting the definition, maintenance and implementation of technology standard

Skills and attributes for success

• Advanced technical proficiency in designing, developing, and debugging solutions
• Advanced knowledge of one or more of: C#/Java or Python
• Bachelor’s degree in computer science, Engineering, IT, Mathematics, or related field preferred
• More than 10 years applied experience
• Significant relevant experience in either an internal or external software or platform engineering role, or similar
• Technical knowledge and experience in delivering software / platform engineering solutions (depending on specialism), providing comprehensive technical advice and handling user requirements
• CI/CD delivery using code management, configuration management and automation tools such as GitHub, ADO
• Proficiency in fine-tuning language models for specific tasks, including text generation, summarization, or question answering
• Knowledge of embedding models and their application in NLP tasks like similarity matching, clustering, and information retrieval
• Familiarity with designing and implementing agentic systems that combine AI models with external tools or environments for autonomous decision-making
• Ability to design robust evaluation frameworks for AI models and agents, including metrics development, A/B testing, and performance benchmarking

Ideally, you’ll also

• Microsoft/Google/AWS certificates
• Delivery using modern methodologies
• Significant proven experience in building application using container-orchestration systems like Kubernetes, and container engines like Docker

Fueled by strategic investment in technology and innovation, Client Technology seeks to drive growth opportunities and solve complex business problems for our clients through building a robust platform for business and powerful product engine that are integral to innovation at scale. You will work with technologists and business specialists, blending EY's deep industry knowledge and innovative ideas with our platforms, capabilities, and technical expertise. As a champion for change and growth, you will be at the forefront of integrating emerging technologies from AI to Agentic Solutions, Data Analytics, and next-generation enterprise protocols into every corner of what we do at EY. That means more growth for you, exciting learning opportunities, career choices, and the chance to make a real impact.

We are looking for a candidate who will be part of the Architecture team within the EY Client Technology's Engineering Architecture Practice. The candidate will be responsible for defining and delivering architectures and designs for business-critical global products and platforms, with focus on scalable distributed systems, cloud-native solutions, modern enterprise architectures, and agentic AI systems. You'll architect solutions hosted in a variety of infrastructure/environments considering reusability, scalability, reliability, observability, and modern design patterns in alignment with EY's mission and strategy. As an architect, you'll embody the principles of the architecture elevator—connecting strategic business vision with hands-on technical implementation while bridging the gap between executive leadership and engineering teams.

You Will

• Build relationships across the business to understand their requirements and strategy, helping them build product/platform roadmaps including agentic AI solutions. Demonstrate architecture leadership to translate business requirements into architecture blueprints and innovative designs incorporating modern distributed systems patterns, microservices architectures, agent orchestration patterns, multi-agent collaboration frameworks, and cloud-native solutions.
• Own the overall technology, architecture and design landscape of products/platforms from solutioning to delivery to adoption phases, with deep understanding of distributed systems, containerization, orchestration platforms, agent frameworks (LangGraph, Microsoft Agent Framework), agent communication protocols (MCP, A2A), reasoning techniques, and enterprise security patterns.
• Design and implement enterprise-scale distributed and agentic AI solutions using modern protocols and frameworks, with expertise in web APIs (REST, GraphQL), Model Context Protocol (MCP), Agent2Agent Protocol (A2A), containerization with Kubernetes, event-driven architectures, and robust access control mechanisms using OAuth 2.0/OpenID Connect, along with AI guardrails using frameworks like NeMo Guardrails, and Guardrails AI.
• Potentially lead engineering teams in a portfolio or large product, set the overall technology and architecture direction and own its end-to-end delivery in a lead architect's capacity. Act as the critical glue between Engineering, Product Management, AI Safety, and Operations teams, ensuring seamless collaboration and alignment across all stakeholders.
• Solve complex problems where scalable solutions may not currently exist, necessitating the ideation and incubation of new distributed system approaches, multi-agent approaches, advanced reasoning patterns, modern architectural patterns, and cutting-edge technologies. Conduct technical feasibility assessments, buy/build analysis for platforms, vendor product evaluations, proof of concepts (with hands-on development) and present various solution options to the business with appropriate recommendations.
• Work closely with multi-disciplinary teams including engineers, AI engineers, prompt engineers, AI safety specialists, data scientists, platform teams, and infosec to deliver modern architectures using optimized delivery approaches, ensuring compliance with enterprise standards, AI governance standards, security policies, and governance guidelines (OWASP GenAI Top 10).
• Provide leadership in product delivery to build and consume reusable functional and technical assets. Identify, define and implement reusable components, API libraries, containerized services, agent templates, reasoning patterns, tool integration libraries, evaluation frameworks, and architectural patterns that can be leveraged across the enterprise.
• Architect and design distributed systems and multi-agent systems that can seamlessly interact with multiple enterprise systems, APIs, and data sources while maintaining security through proper authentication implementation and AI safety through guardrail implementation, scalability through containerization and Kubernetes orchestration, and reliability through event-driven architecture patterns and observability via Open Telemetry evolving AI standards
• Provide support to product and project managers in building plans, forecasts, estimations and costs for new products/platforms, including considerations for infrastructure resources, LLM API costs, token usage optimization, containerization costs, and ongoing platform operational requirements.
• Provide coaching, mentoring and support to development teams during the delivery phase across the ecosystem, frameworks and platforms. Ensure that developed artifacts comply with envisioned architecture and design, expected quality, security standards, AI safety standards, and recommended development practices through code reviews, prompt reviews, agent workflow validation, and architecture validation processes.
• Can work across multiple projects with varied stakeholders, operating as the architecture elevator that connects boardroom strategy with server room implementation. An architect sets architectural direction for scalable systems, builds consensus around technology strategy, mediates conflicts regarding implementation approaches, and provides technical leadership and advisory services while ensuring alignment between Engineering, Product Management, AI Safety, and Operations teams.
• Demonstrate excellent interpersonal communication and organizational skills required to operate as a leading member of global, distributed engineering teams. Excel at translating complex technical concepts (including agentic AI concepts) to business stakeholders and business requirements to engineering teams.
• Cultivate lasting relationships across business, IT, technology vendors, and industry experts to maintain insight into the broader technology landscape and agentic AI landscape as well as emerging trends. Understand new trends and emerging technologies in multi-agent systems, reasoning techniques, AI safety, agent protocols, and how they apply to EY's business context.

To Qualify for the Role, You Must Have
Architecture & Leadership

• Led and governed global engineering teams and architects, driving the technology and architecture landscape of large and complex portfolios of products/solutions/projects, achieving measurable success in implementation and enterprise adoption. Demonstrated experience as an architecture elevator, connecting strategic business vision with hands-on technical execution.
• Expert-level proficiency in at least one of the following programming languages: C#, Java, JavaScript, TypeScript, or Python, with demonstrated ability to architect and implement enterprise-scale solutions including AI-powered systems using your chosen language stack.
• Deep hands-on experience with modern protocols and frameworks including web APIs (REST, GraphQL), containerization technologies (Docker, Kubernetes), event-driven architecture patterns, enterprise security implementations using OAuth 2.0/OpenID Connect, and emerging AI protocols such as Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication frameworks. Proven ability to design and implement enterprise-scale distributed solutions.
• Architecture leadership skills with advanced understanding and practical experience in modern architecture patterns, with proven track record in complex, large-scale implementations serving user bases in the hundreds of thousands or more across the entire product lifecycle. Experience leading engineering teams and acting as the critical connector between Engineering, Product Management, and Operations.
• Hands-on deep experience in architecture including application integration, cloud infrastructure architecture, data pipelines, security architectures, and successful delivery of both functional and non-functional aspects of platforms using cloud-native services, full-stack applications, DevSecOps, security practices, and automated deployment pipelines.
• Comprehensive knowledge of modern enterprise technologies including web APIs, microservices architectures, containerization and orchestration platforms (Docker, Kubernetes), event-driven systems, message queuing, and enterprise security patterns including OAuth 2.0, OpenID Connect, and identity management solutions.
• Deep understanding of distributed system architectures, multi-service systems, API gateway patterns, and the ability to design scalable systems that can handle complex enterprise workloads with proper load balancing, caching strategies, and fault tolerance across enterprise environments.
• Expert knowledge of data management including relational and NoSQL databases, data streaming platforms, real-time data processing, and data governance. Understanding of platform lifecycle management, A/B testing strategies, and performance monitoring.
• Strong background in security best practices, enterprise compliance requirements, and regulatory standards in enterprise environments.

Agentic AI & Advanced AI Systems

• 2+ years of hands-on experience architecting and implementing enterprise-scale agentic AI systems, with proven track record in designing and deploying multi-agent systems and AI orchestration platforms serving significant user bases.
• Expert-level proficiency in major agent frameworks including LangChain/LangGraph (stateful graph-based agent workflows), Microsoft Ecosystem (AutoGen for multi-agent systems, Semantic Kernel, migration to Microsoft Agent Framework). Experience with at least 2+ different agent orchestration frameworks in production environments.
• Expertise in agent communication protocols and standards: Model Context Protocol (MCP), Agent2Agent Protocol (A2A), AG-UI event-based protocols, OpenAPI, JSON-RPC, Server-Sent Events (SSE), and WebSockets for agent integration.
• Knowledge of advanced reasoning techniques with production implementation experience: ReAct (Reasoning + Acting), Chain-of-Thought (CoT), and Tree of Thoughts (ToT). Expert knowledge of planning patterns including Multi-Plan Selection, External Module-Aided Planning, Memory-Augmented Planning, and Task Decomposition.
• Hands-on experience with AI safety frameworks and guardrail implementation: NeMo Guardrails (NVIDIA), Guardrails AI, Azure AI Content Safety or equivalent enterprise platforms. Proven experience implementing multi-layer guardrail strategies including input guardrails (prompt injection detection, jailbreak prevention, PII masking), output guardrails (hallucination detection, toxicity screening, fact-checking), runtime guardrails (token-level monitoring, confidence scoring, circuit breakers), and interaction-level guardrails (tool use restrictions, decision caps, human-in-the-loop gates).
• Experience with LLM evaluation frameworks: DeepEval, RAGAS, LangSmith. Knowledge of evaluation methodologies including LLM-as-a-Judge patterns, Human-in-the-Loop (HITL) annotation and feedback systems, and A/B testing for agent/prompt variants. Deep understanding of key metrics including performance, efficiency, quality, and safety metrics.
• Production observability implementation: Span-level tracking and distributed tracing for multi-agent systems, cost attribution and token counting, prompt version control, real-time quality monitoring, and user feedback loops.
• Expert-level skills in RAG (Retrieval-Augmented Generation) architectures: Agentic RAG, GraphRAG, Multi-Modal RAG. Production experience with two or more vector databases (MongoDB Atlas Vector Search, Redis, Pinecone, Chroma). Deep understanding of memory architectures for agents including working memory, persistent memory, semantic memory, and episodic memory.
• Proven experience designing and implementing multi-agent systems: Agent coordination mechanisms, inter-agent messaging, shared knowledge bases, collaborative memory, task delegation and work distribution algorithms. Mastery of orchestration patterns including sequential, concurrent, and hierarchical orchestration, dynamic handoff and context-based routing, human-in-the-loop integration, and event-driven agent orchestration.
• Cost optimization expertise: Token usage optimization, model selection strategies, and ROI analysis for agentic AI systems.
• Demonstrated passion for AI technologies and their potential to transform enterprise solutions, with eagerness to stay current with AI advancements and integrate them thoughtfully into architectural decisions.
• Strong background in modern software architecture patterns including event-driven architectures, data streaming, real-time processing, and microservices-based platforms.

Ideally, You'll Also Have

• Bachelor's or Master's Degree in Engineering, Computer Science, Data Science, AI/ML, Mathematics, or related technical field.
• 15+ years overall IT industry experience, and 5+ years in architect roles, including experience with enterprise platform implementations, distributed system deployments, multi-agent system deployments, and leading cross-functional engineering teams.
• Achieved one or more relevant certifications such as Microsoft Azure Solutions Architect, Microsoft Azure AI Engineer Associate, AWS Solutions Architect, Google Cloud Professional Architect, Google Cloud Professional AI Engineer, TOGAF, Kubernetes certifications (CKA, CKAD), DeepLearning.AI specializations, or emerging distributed systems architecture certifications.
• Experience with modern development frameworks and tools such as container orchestration platforms, API management tools, service mesh technologies, or similar distributed systems development ecosystems.
• Thought leadership in technology and agentic AI - presenting ideas, products, research papers, and concept papers to varied audiences at AI conferences, building technology points of view and presenting them in industry forums/events, contributing to open-source projects, and published research on AI.
• Experience in designing and implementing business use-cases using low-code/no-code platforms, data reporting, data management and governance technologies, mobile applications, and deep cloud security concepts.
• Experience with specialized agentic AI capabilities: Multi-modal agents (text, vision, audio, video processing), code generation agents (automated programming, code review, bug detection), and domain-specific agents (finance, healthcare, legal, customer service).
• Knowledge of enterprise security including OAuth 2.0/OpenID Connect implementation, API security, container security, and secure deployment practices.

What We Look For

We want people who are self-starters with a passion for modern technology innovation and agentic AI innovation, who can take initiative in rapidly evolving technology landscapes and drive digital transformation and AI transformation initiatives. If you can think critically and creatively to solve complex problems using modern distributed systems technologies, multi-agent systems, advanced reasoning techniques, and enterprise-grade AI safety frameworks, and can envision how scalable architectures and intelligent agents can transform enterprise operations, you will excel.

You should be comfortable working with culturally diverse teams including engineers, AI engineers, AI safety specialists, platform specialists, data scientists, and offshore development teams, which means you may need to work outside normal hours to collaborate with global engineering teams. Some travel may be required for technology conferences, AI conferences, client implementations, and international project collaboration.

You must demonstrate a deep commitment to AI safety and responsible AI practices, understanding that enterprise agentic AI systems require robust guardrails, continuous monitoring, and adherence to emerging regulatory frameworks. You should be comfortable balancing innovation velocity with safety, governance, and compliance requirements.

What we offer you

The compensation ranges below are provided in order to comply with United States pay transparency laws. Other geographies will follow their local salary guidelines, which may not be a direct conversion of published US salary ranges.At EY, we’ll develop you with future-focused skills and equip you with world-class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn.

• We offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $138,200 to $266,000. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $165,800 to $302,300. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
• Join us in our team-led and leader-enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.
• Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances. You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.

Are you ready to shape your future with confidence? Apply today.
EY accepts applications for this position on an on-going basis.

For those living in California, please click for additional information.

EY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law.

EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY’s Talent Shared Services Team (TSS) or email the TSS at .

Technology – Data and Decision Science – Data Engineering – Manager

In this role, you will design and build analytics solutions that deliver significant business value. You will collaborate with other data and analytics professionals, management, and stakeholders to ensure that business requirements are translated into effective technical solutions. Key responsibilities include:

• Understanding and analyzing business requirements to translate them into technical requirements.
• Designing, building, and operating scalable data architecture and modeling solutions.
• Staying up to date with the latest trends and emerging technologies to maintain a competitive edge.

Key Responsibilities:

As a Data Engineering Manager, you will play a crucial role in managing and delivering complex technical initiatives. Your time will be spent across various responsibilities, including:

• Leading workstream delivery and ensuring quality in all processes.
• Engaging with clients on a daily basis, actively participating in working sessions, and identifying opportunities for additional services.
• Implementing resource plans and budgets while managing engagement economics.

This role offers the opportunity to work in a dynamic environment where you will face challenges that require innovative solutions. You will learn and grow as you guide others and interpret internal and external issues to recommend quality solutions. Travel may be required regularly based on client needs.

Skills and attributes for success:

To thrive in this role, you should possess a blend of technical and interpersonal skills. The following attributes will make a significant impact:

• Lead the design and development of scalable data engineering solutions using Databricks on cloud platforms (e.g., AWS, Azure, GCP).
• Oversee the architecture of complex cloud analytics solutions, ensuring alignment with business objectives and best practices.
• Manage and mentor a team of data engineers, fostering a culture of innovation, collaboration, and continuous improvement.
• Collaborate with clients to understand their analytics needs and deliver tailored solutions that drive business value.
• Ensure the quality, integrity, and security of data throughout the data lifecycle, implementing best practices in data governance.
• Drive end-to-end data pipeline development, including data ingestion, transformation, and storage, leveraging Databricks and other cloud services.
• Communicate effectively with stakeholders, including technical and non-technical audiences, to convey complex data concepts and project progress.
• Manage client relationships and expectations, ensuring high levels of satisfaction and engagement.
• Stay abreast of the latest trends and technologies in data engineering, cloud computing, and analytics.
• Strong analytical and problem-solving abilities.
• Excellent communication skills, with the ability to convey complex information clearly.
• Proven experience in managing and delivering projects effectively.
• Ability to build and manage relationships with clients and stakeholders.

To qualify for the role, you must have:

• Bachelor’s degree in computer science, Engineering, or a related field required; Master’s degree preferred.
• Typically, no less than 4 - 6 years relevant experience in data engineering, with a focus on cloud data solutions and analytics.
• Proven expertise in Databricks and experience with Spark for big data processing.
• Strong background in data architecture and design, with experience in building complex cloud analytics solutions.
• Experience in leading and managing teams, with a focus on mentoring and developing talent.
• Strong programming skills in languages such as Python, Scala, or SQL.
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Strong communication and interpersonal skills, with a focus on client management.

Required Expertise for Managerial Role:

• Strategic Leadership: Ability to align data engineering initiatives with organizational goals and drive strategic vision.
• Project Management: Experience in managing multiple projects and teams, ensuring timely delivery and adherence to project scope.
• Stakeholder Engagement: Proficiency in engaging with various stakeholders, including executives, to understand their needs and present solutions effectively.
• Change Management: Skills in guiding clients through change processes related to data transformation and technology adoption.
• Risk Management: Ability to identify potential risks in data projects and develop mitigation strategies.
• Technical Leadership: Experience in leading technical discussions and making architectural decisions that impact project outcomes.
• Documentation and Reporting: Proficiency in creating comprehensive documentation and reports to communicate project progress and outcomes to clients.

Large-Scale Implementation Programs:

1. Enterprise Data Lake Implementation: Led the design and deployment of a cloud-based data lake solution for a Fortune 500 retail client, integrating data from multiple sources (e.g., ERPs, POS systems, e-commerce platforms) to enable advanced analytics and reporting capabilities.
2. Real-Time Analytics Platform: Managed the development of a real-time analytics platform using Databricks for a financial services organization, enabling real-time fraud detection and risk assessment through streaming data ingestion and processing.
3. Data Warehouse Modernization: Oversaw the modernization of a legacy data warehouse to a cloud-native architecture for a healthcare provider, implementing ETL processes with Databricks and improving data accessibility for analytics and reporting.

Ideally, you’ll also have:

• Experience with advanced data analytics tools and techniques.
• Familiarity with machine learning concepts and applications.
• Knowledge of industry trends and best practices in data engineering.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their data services.
• Knowledge of data governance and compliance standards.
• Experience with machine learning frameworks and tools.

We’re looking for a Senior DevOps Engineer to build and run cloud and AI infrastructure at scale. You’ll own IaC with Terraform, CI/CD, Kubernetes, and Linux. You’ll also help runboth in Azure and locally (Ollama/vLLM/llama.cpp). Your work will enable fast, secure, repeatable delivery.

Key responsibilities

• Build and maintain Azure infrastructure with Terraform (modules, workspaces, pipelines, policies).
• Design and operate CI/CD with GitHub Actions and/or Azure DevOps (multi-stage, approvals, environments).
• Run containers and Kubernetes/AKS (Helm, ingress, autoscaling, node pools, storage).
• Manage AI/LLM runtime: local model runners (Ollama, vLLM, llama.cpp), GPU/CPU configs.
• Support RAG : embeddings pipelines, vector DBs (Azure AI Search/Cognitive Search, pgvector, Milvus), data sync, retention.
• Automate platform tasks with Python (tooling, CLI utilities, API glue, ops scripts).
• Implement observability (Azure Monitor, Prometheus/Grafana, logs/traces/metrics, alerts, runbooks, SLOs).
• Apply Zero Trust security; Enforce least privilege and role-based access control (RBAC), Identity-based segmentation (Azure AD, Conditional Access, MFA).
• Implement policy-as-code (OPA, Azure Policy) for compliance.
• Rotate secrets and certificates via Key Vault; integrate with pipelines.
• Add continuous security scanning (SAST/DAST, container image scanning).
• Handle reliability: rollout strategies, health probes, incident response, postmortems.
• Optimize costs: right-sizing, autoscaling, budgets, tags, reporting.

Key requirements:

• 4+ years in DevOps/SRE/Platform Engineering.
• Strong Linux (shell, systemd, networking, performance troubleshooting).
• Terraform at scale (modules, state backends, CI/CD integration).
• Deep Azure experience (AKS, VNets, Key Vault, Storage, Monitor, Identity, Networking).
• CI/CD expertise (GitHub Actions and/or Azure DevOps).
• Containers and Kubernetes in production.
• Python or scripting for automation (solid scripting and tooling; not full-time app dev).
• Hands-on with LLM setups (local runners or Azure OpenAI), embeddings, vector indexes, and RAG basics.

Nice to have

• Multi-cloud exposure ( AWS / GCP ).
• Azure AI services (Azure OpenAI, Cognitive Search).
• GitOps (Argo CD/Flux), Helm packaging, OCI registries.
• Eventing/queues (Event Grid, Service Bus, Kafka).
• Security/compliance in cloud (CIS, NIST, Microsoft CAF).
• Certifications: AZ‑104, AZ‑204, AZ‑400 , AI‑900 , HashiCorp Terraform Associate , CKA/CKAD .
• Experience with GPU nodes, drivers, CUDA/ROCm, or CPU-only optimizations for LLMs.

How we work

• Everything as code. PRs, reviews, and tests.
• Small batches. Trunk-based or short-lived branches.
• Clear runbooks and on-call rotation where needed.
• Measure, alert, fix, and improve.

Full time employment, Monday – Friday, 40 hours per week, 8:30 am – 5:30 pm.

MINIMUM REQUIREMENTS:

Must have a Bachelor’s degree in Computer Science, Data Science, Information Technology, Engineering, Mathematics, Statistics, Machine Learning, Management Information Systems (MIS), or a related field and 5 years of progressive, post-baccalaureate work experience. Alternatively, will accept a Master’s degree in Computer Science, Data Science, Information Technology, Engineering, Mathematics, Statistics, Machine Learning, Management Information Systems (MIS), or a related field and 4 years of work experience.

Must have 4 years of experience in quantitative modeling and analysis focusing on big-data problem solving to collect, analyze, and present findings and solutions.

Must have 4 years of hands-on experience in python and SQL.

Must have 3 years of experience in one or a combination of any of the following cloud platforms:
o Azure
o Amazon
o Google

Must have 4 years of experience in navigating database models to build data sets for analytics and model training and development.

Must have 2 years of experience modelling data in Power BI and other PowerApps.

Must have 1 year of experience in the delivery of intelligent automation services and the technology life cycle, including operating model/strategy, opportunity assessment, discovery and requirements definition, solution architecture and design, development, testing and production release.

Must have 1 year of experience in quantitative analysis using Agile methodologies or robotics tool-specific methodologies.

Must have 3 years of experience with data manipulation tools and libraries SQL, Pandas, or Spark.

Must have 1 year of experience with containerization and scaling models as well as integrating models and feedback from downstream consumption systems.

Employer will accept any suitable combination of education, training, or experience.