Lead Devops Engineer - Ai Research Incubation jobs at Salesforce in United States, Palo Alto

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In this role, you will play a pivotal part in accelerating the work of our researchers and data collection teams by building tools and infrastructure that streamline the end-to-end process of collecting, annotating, and managing AI agent data. You will collaborate closely with researchers and data scientists to transform early research ideas into robust incubation products, contributing to both backend services and frontend interfaces that support internal workflows and pilot customer deployments. By implementing state-of-the-art research into production-quality demo prototypes, you will help bridge the gap between cutting-edge innovation and real-world impact—bringing research to life in ways that inform product direction and deliver tangible value to the broader AI ecosystem.
Required Skills:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
• 5+ years of professional experience as a fullstack engineer or software developer
• Experience building internal tools or UIs for data labeling, annotation, or human-in-the-loop workflows
• Proficiency in building and integrating RESTful APIs, with experience using modern JavaScript frameworks such as React
• Strong knowledge of object-oriented programming and fluency in at least one core language (e.g., Python, Java, JavaScript, C++)
• High proficiency in at least one backend web framework (e.g., Node.js with Express, Python withFlask/FastAPI/Django)
• Solid understanding of frontend technologies including JavaScript, CSS, HTML5, and asynchronous communication (e.g., JSON, AJAX)
• Familiarity with database design and query optimization using relational databases (e.g., PostgreSQL, MySQL)
• Experience with automated testing frameworks for unit, integration, and end-to-end testing
• Excellent communication and collaboration skills, especially when working with cross-functional teams including researchers and data scientists

Preferred Skills:

• Experience working with LLMs, agent frameworks, or retrieval-augmented generation (RAG) systems
• Familiarity with Python-based AI research tooling (e.g., LangChain, LlamaIndex, Hugging Face Transformers)
• Experience designing, maintaining, and scaling structured or semi-structured data pipelines
• Experience deploying fullstack applications using Docker and cloud platforms (e.g., AWS, GCP, or Azure)
• Demonstrated ability to turn research papers or models into interactive prototypes or product-ready demos
• Experience building robust internal systems and user-facing tools for research or experimentation
• Familiarity with Agile development processes and a strong bias toward rapid iteration and continuous improvement

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Posting Statement

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You will be working cross-functionally with engineers, architects, and product managers to build the breakthrough features that our internal customers will love, adopt and use while ensuring stable and scalable applications. You will also be working with data scientists to innovate and deliver distributed backend technologies, sometimes including big data technologies. You'll be a part of a modern, lean, self-governing product engineering team where you have the ability to switch hats between coding to requirements gathering, to testing for quality and performance.

CECM develops intelligent,

We are looking for a Lead Engineer who can drive our strategy for optimizing cost efficiency and improving utilization across all of the Salesforce services. You will not only provide visibility into opportunities to improve availability, but also work with multiple service owners to help and guide delivering on those optimizations.

Your Responsibilities

• Drive capacity visibility and automation improvements across multiple services at Salesforce

• Lead software development being delivered by multiple engineers

• Lead and participate in requirement gathering, design, and development of complex systems

• Independently design and deliver analytics tools and frameworks for diverse users, including other engineers, data scientists, and domain experts

• Mentor team members in all aspects of the software development lifecycle

• Master our code base, then improve it

• Build resilient, automated systems and assessing and integrating best-in-class technologies when appropriate

Required Skills

• Bachelor’s degree in Computer Science and 8+ years of experience, or equivalent industry experience

• Deep knowledge of two or more functional or scripting programming languages: Python, Scala, or equivalent

• Experience operating time-series forecasting, anomaly detection and AI integrated products in production environments

• Extensive experience working with Data Scientists and operating ML models in production services

• Understanding of Data Science, Machine Learning and AI concepts

• Extensive experience with distributed services (REST, rpc or similar APIs) and relational databases (Postgres or similar)

• Experience with orchestration and workflow management tools, i.e. Airflow

• Experience with distributed compute platforms like Trino or Spark

• Experience with Agile development methodology, Test-Driven Development, incremental delivery, and CI/CD

• Experience owning and operating services throughout the software development lifecycle including design, development, release and maintenance.

• Experience communicating technical vision, mentoring junior engineers and managing projects.

Specialization in one of the following areas:

• Interest infrontend/visualizationdevelopment (Tableau, JavaScript)

• Experienced in infrastructure automation and cloud platforms: AWS, Azure, or GCP

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Posting Statement

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You will lead the design and implementation of tools and frameworks that ensure our AI systems are fair, accountable, and transparent. Using advanced machine learning techniques, you’ll generate actionable insights, drive research excellence, and support responsible AI practices across the full development lifecycle—from experimentation to production deployment.

Job Responsibilities:

• Analyze data and models to identify potential trust and safety issues; define testing protocols for different data types and model architectures; recommend mitigation strategies, tooling investments, and safe thresholds for deployment.
• Define technical goals and guide research/engineering teams on responsible AI best practices. Offer development support and thought leadership on critical ethical tradeoffs in algorithmic design.
• Contribute to the development and adoption of libraries and tools that support evaluation, testing, and mitigation of risks. Build features that enhance explainability and user trust in model outputs.

• Collaborate with industry leaders in similar positions in peer organizations on ways to improve the state of responsible AI development.

Minimum Qualifications:

• Practical experience in machine learning

• MS or Ph.D. in a quantitative discipline with 8+ years of experience or a BS in a quantitative discipline with 10+ years of experience.

• Fluent in building/prototyping machine learning models and algorithms and wrangling large datasets.

• Proficient in using Python and common machine learning frameworks (e.g., TensorFlow, PyTorch) and AI tools (e.g., cursor, W&B, huggingface) to implement models and algorithms.

• Proficient in SQL, shell scripting, and Unix/Linux command-line tools.

• Up to date on the evolution of trusted AI and ability to meet both state-of-the-art and global standards for

• evaluation, particularly in generative AI

• Experience working across teams of engineers, data scientists, and researchers.

• Strong communication skills. Comfortable presenting ideas to peers, cross-functional groups, and executives in multiple formats, from slide decks to informal chats.

• Earns trust in relationships both internally and externally, and at all levels of the organization. Challenges the status quo to improve the productivity, effectiveness, and culture of a team - without burning bridges.

• Ability to creatively prioritize, stage, and sequence solutions to challenging/complex problems.

• Demonstrated experience with actually shipping code, getting data science into production

• Ability to stay abreast of the latest findings in the field, new technologies, and best practices

• Passion for the idea that technology can be a force for social good and for ethics and fairness.

Preferred Qualifications:

• 10+ years of business experience

• Experience with designing and building micro-services, familiar withKubernetes/containerization/RESTfulAPI/gRPC, etc.

• Strong experience leading multi-disciplinary teams driving significant business results

• Knowledge of enterprise SaaS space

• Strong publications at top AI conferences

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Posting Statement

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,,, a groundbreaking suite of

In this role, you will drive the development of agentic Search and Knowledge Graph solutions at scale, integrating the latest advancements in machine learning, LLMs, and vector databases. You will be responsible for leading the end-to-end AI lifecycle, from conceptualization through production, focusing on scalable search and retrieval architectures optimized for enterprise use cases. As a motivated leader with a point of view, you will define standard methodologies and collaborate closely with Product Managers, Data Scientists, and Research teams to shape and deliver groundbreaking AI experiences.

• Lead the Architecture of Sophisticated Search & Knowledge Graph Solutions
  Architect and implement end-to-end, large scale search and retrieval solutions that demonstrate Knowledge Graphs and are optimized for high-performance, multi-tenant environments.
• Develop Intelligent Retrieval Pipelines
  Innovate hybrid retrieval pipelines combining semantic, vector, and symbolic search to improve contextual relevance, speed, and accuracy in knowledge driven AI applications.
• Optimize and Automate Search Systems
  Enhance system efficiency through automation in demand forecasting, configuration, and proactive monitoring, driving real time search optimization.
• Collaborate Across Teams for AI Driven Product Innovation
  Work closely with multi-functional teams, including Product Managers, Knowledge Engineers, and ML Researchers, to assemble requirements and translate them into scalable, innovative search and retrieval solutions.
• Pioneer Search and Knowledge Graph Innovations
  Guide discussions on emerging technologies and advancements in vector search, graph embeddings, and knowledge augmented retrieval, valuing continuous innovation.

• 5+ years in Machine Learning & Search Systems
  Extensive experience with large-scale search, Machine Learning, and knowledge driven systems, specifically focused on integrating Knowledge Graphs, search optimization, and sophisticated retrieval techniques.
• Expertise in Semantic and Vector-Based Search
  Deep knowledge of vector databases (e.g., FAISS, Pinecone, Milvus), approximate nearest neighbor (ANN) search algorithms, and embedding techniques to power high relevance search systems.
• Strong Background in NLP & LLMs
  Experience with natural language processing (NLP), prompt engineering, and applying LLMs to enhance knowledge based search and retrieval in enterprise contexts.
• Sophisticated Knowledge Graph Skills
  Proficiency in graph databases (e.g., Neo4j, Amazon Neptune), graph embedding, and linking techniques to enable rich contextual search and high dimensional graph-based retrieval.
• Proficiency in Distributed Systems & ML Frameworks
  Authority understanding of distributed systems, data streaming (e.g., Kafka, Spark), and Machine Learning frameworks (TensorFlow, PyTorch) to support realtime, resilient AI applications.
• Programming Mastery in Python & Graph Based Frameworks
  Strong programming skills in Python, with expertise in machine learning and graph-based frameworks to facilitate scalable, high-performance AI solutions.

• Experience with Multi-Stage Retrieval Pipelines
  Hands-on experience in designing and optimizing multi-stage retrieval workflows that balance precision, recall, and relevance at scale.
• In-Depth Knowledge of Re-Ranking & Retrieval Optimization
  Expertise in retrieval-specific optimizations, including re-ranking, hybrid search, and knowledge augmented retrieval, to improve relevance in enterprise-scale systems.
• Graph Embedding & Contextual Retrieval Expertise
  Confirmed skills in graph based search, context expansion techniques, and Knowledge Graph integration to enhance retrieval depth and accuracy.
• Knowledge Graph Curation & Ontology Management
  Experience in Knowledge Graph curation, schema design, and ontology management, ensuring efficient and adaptable knowledge driven search solutions.
• Familiarity with Feedback Loops and Fine-Tuning
  Knowledge of incorporating user feedback and relevance signals to fine-tune contextual embeddings and improve Search and Knowledge Graph system performance.

• Broad ML Experience with Diverse Approaches
  Strong foundation in diverse ML techniques, from neural networks to probabilistic models, adaptable for Search and Knowledge Graph-centric AI use cases.
• Exceptional Communication and Collaboration Skills
  Outstanding written and verbal communication abilities, with confirmed expertise in collaborating across engineering, research, and product teams.

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Posting Statement

does not accept unsolicited headhunter and agency resumes.

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You will build tools that help build and test AI agents that will be used by thousands of end users, delivering value with AI automation. Our software engineers ship applications written in the enterprise Java stack on the core platform and on our Agentforce platform. We work in a highly collaborative environment, and you will liase with a highly cross functional team comprised of Software Engineers, Machine learning engineers, UX experts, product managers to build AI Agent tooling. We value execution, clear communication, in person collaboration, and making learning fun.As part of this role, you will:

• Design, implement, test and deliver highly scalable application code

• Build on top of the Agentforce platform, delivering true next-generation AI Agent tools

• Master our development process, platform, culture and code base, then improve it

• Present your own designs to internal/external groups and review designs of others

• Develop test strategies, design automation frameworks, write unit/functional tests to drive up code coverage and automation metrics

• Participate in the team’s on-call rotation to address sophisticated problems in real-time and keep services operational and highly available

• Troubleshoot production issues.

Required Skills:

• 4+ years of professional software development experience

• Deep knowledge of object oriented programming and experience with at least one object oriented programming language preferably Java

• Expertise in developing software for Generative AI applications

• Beginners mindset with proven experience shipping quick turnaround incubation projects

• High proficiency in at least one high-level programming language and web framework (NodeJS, Express, Hapi, etc.)

• Proven understanding of web technologies, such as JavaScript, CSS, HTML5, XML, JavaScript, JSON, and/or Ajax

• Validated understanding of Database technologies such as SQL, PL/SQL and relational database schema design

• Experience in automated testing including unit and functional testing using Java, JUnit, JSUnit, Selenium

Preferred Skills:

• Bachelor's degree in Computer Science or equivalent field

• Prior experience in prompt engineering, multi-agent interaction or Task planning with LLM based agents

• Solid experience in fullstack software development, including UI tier, API development, metadata management, and/or client SDKs development

• Experience with Agile software development and test-driven development.

• Ability to support/resolve production customer escalations with excellent debugging and problem solving skills

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Posting Statement

does not accept unsolicited headhunter and agency resumes.

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Responsibilities:

• Own and pursue ambitious, long-term research goals.
• Develop solutions for real-world, large-scale problems.
• As needed lead teams to deliver on more complex pure and applied research projects.

Minimum qualifications:

• Ph.D./Master's degree in computer science, artificial intelligence, machine learning, or a related technical field.

• Strong publication record in top AI venues like NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, ECCV, and ICCV.

• Experience with one or more general-purpose programming languages, including but not limited to C/C++ or Python.

• Experience with one or more deep learning libraries and platforms (e.g., TensorFlow, Jax, or PyTorch).

• Proven ability to implement, operate, and deliver results via innovation at a large scale.

• Large Language Models (LLMs), LLM evaluation and benchmarking, multilingual LLMs, LLMs as foundation of agents

Preferred qualifications:

• Full-time industry experience in deep learning research/product.
• Strong experience building and applying machine learning models for business applications.
• Experience training large language models.
• Experience mentoring and advising other researchers.
• Strong programming skills, competitive in ACM-ICPC or other competitions or open source experience is preferred.
• Experience in implementing high-performance and large-scale deep learning systems.
• Thoughtful about AI impacts and ethics.
• Fantastic problem solver; ability to solve problems the world has not solved before.
• Excellent written and spoken communication skills.
• Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams.

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Posting Statement

does not accept unsolicited headhunter and agency resumes.

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Job Details

About the Role

Key Responsibilities
Design, implement, and manage cloud infrastructure (AWS, GCP) including networking, security, and compute resources.
Develop and maintain CI/CD pipelines to automate deployment and testing of AI models and applications.
Build, manage, and optimize Kubernetes clusters for deploying AI services and research applications.
Implement infrastructure as code (IaC) using Terraform and Helm to ensure repeatable and scalable deployments.
Automate system operations and monitoring using Python and shell scripting.
Ensure security standard methodologies across cloud environments, including firewall and access control management.
Solve infrastructure issues and optimize system performance.
Collaborate with AI researchers and software engineers to streamline model deployment and integration.
Task about managing databases (SQL and No-SQL), including database provisioning, performance tuning, and backup strategies.
Ensure database security, replication, and high availability across cloud environments.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or a related field.
• 3+ years of experience in DevOps, cloud infrastructure, or site reliability engineering.
• Strong experience with AWS and GCP, including DNS, VM management, networking, Kubernetes, and firewall security.
• Proficiency in CI/CD pipeline development and automation (GitHub Actions, Jenkins, GitLab CI/CD, etc.).
• Expertise in Docker, Kubernetes, and Helm for container orchestration and deployment.
• Hands-on experience with Terraform for infrastructure provisioning and management.
• Strong scripting skills in Python and shell scripting for automation.
• Solid understanding of networking, security standard processes, and cloud monitoring tools.
• Excellent troubleshooting and problem-solving skills.

Preferred Qualifications

• Experience with AI/ML model deployment and pipeline automation.
• Knowledge of logging and monitoring tools (Prometheus, Grafana, ELK stack, etc.).
• Familiarity with serverless computing and cloud-native application design.
• Contributions to open-source DevOps tools or frameworks.
• Experience with Salesforce Falcon is a plus.

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Posting Statement

does not accept unsolicited headhunter and agency resumes.