דרושים Director Buyer Experience Ai Rd ב-איביי ב-India, Bengaluru

As a thousands of applications and support 3,000+ developers every day. You’ll build paved‑path tooling, automate at scale, and adopt modern cloud infrastructure so teams can develop, test, and ship high‑quality, secure, performant software—rapidly and reliably.

• Own the Software Build, Test platform and frameworks. Design and evolve fast, reproducible, and cache-efficient builds; reduce CI build times with creative solutions; improve correctness and remove flakiness in infrastructure; maintain scalable artifact storage and dependency management.

• Platform modernization. Our platform is powered by Jenkins, Maven for Java, NPM for NodeJs builds. You’ll be evaluating state of the art CI platforms (e.g.Tekton) and pave the way for modernizing our Build, Test stack.

• Spin up ephemeral, production-like test environments. Standardize on sandboxed, on-demand environments (e.g., per-PR) to enable reliable integration/e2e testing and preview deployments.

• Harden & simplify deployments. Advance our CD/GitOps workflows (progressive delivery, automated rollbacks, canaries), with golden paths and strong guardrails.

• Build the internal developer portal. Curate paved roads for services, data, and infra via templates, scorecards, and software catalogs to improve discoverability and self-service.

• Introduce AI-assisted engineering.

  • Ship secure, private AI copilots for code authoring, refactoring, and code review.

  • Use LLMs for test generation , flaky test triage , log summarization , debug suggestions , Error classifications, Selective Test Execution and AIOps across CI/CD.

  • Build evaluation harnesses, prompt libraries, RAG over internal docs, and policy controls for IP, PII, and secrets.

• Champion reliability, security & compliance. Bake in supply-chain security (SBOMs, provenance, signing), policy-as-code, and infra guardrails, Patching CVEs in accordance with policies

• Instrument, measure, improve. Track DORA and DevEx metrics (lead time, deployment frequency, change-failure rate, MTTR) and drive continuous improvement via experiments.

• Partner widely. Work with product teams, Cloud, Frameworks, Security, and Data/ML to understand friction points and design paved-road solutions that scale.

• Collaborate across.

• Data driven analysis and cut average CI build times by 40% via incremental builds, dependency management and smarter caching; Bring down slowest test suites with parallelization, Selective Test executions, profiling and flake-busting.

• Launch ephemeral “PR environments” with seeded data and synthetic traffic; integrate with feature flags for safe, progressive rollouts.

• Stand up an internal developer portal (service templates, scorecards, docs search) and migrate golden paths there.

• Deliver an AI DevEx toolkit : repo-aware chat, code-review assistant, flaky-test explainer, and CI log summarizer—with evaluation dashboards and privacy controls.

• Pilot remote dev pods
  

Must-haves

• 7+ years building platforms/tools for large engineering orgs; deep expertise in one or more build systems (preferably building Java, Nodejs stacks), CI orchestration (preferably Jenkins), test infra, deployment/CD pipelines, or Internal Developer Portals.

• Self-starter with a proactive mindset and strong sense of ownership.

• Proven ability to manage communications effectively with partner teams across global regions, with hands-on experience working in private cloud environments.

• Skilled at designing robust solutions while proactively anticipating potential issues to ensure reliability and efficiency.

• Strong systems design for high-scale developer workflows (monorepos/multirepos, artifact caching, remote execution, hermetic builds).

• Experienced in providing timely solutions to developer challenges in Jenkins environments, ensuring smooth CI/CD workflows.

• DevOps fundamentals: Containers, Kubernetes, service mesh, IaC (Terraform), GitOps, observability (metrics/logs/traces), SLOs/SLIs.

• Practical AI skills & design patterns: Prompt engineering, hands-on RAG, LLM evaluations, API orchestration, privacy/guardrails; ability to ship AI-backed tools that measurably reduce toil.

• System design & design patterns: strong grasp of distributed systems, API design, resiliency, and object-oriented/functional patterns; ability to create clear, scalable architectures and ADRs.

• Agentic/MCP architectures: practical experience designing agent loops (planner/executor/critic), tool abstractions, memory, and MCP-style tool/resource servers for enterprise integration.

• Proficiency in at least two languages (e.g., Java, Kotlin, Python, Go,). Fullstack development experience is a plus.

• Fluency in Linux/Ubuntu commands to get bottom of the system level issues.

• Database literacy: working knowledge of NoSQL and modern relational databases.

• Observability dashboards: ability to build with Prometheus, Grafana, ELK, Splunk, New Relic, or Nagios.

• Performance sleuthing: able to diagnose system and web-service performance issues end-to-end.

Nice-to-haves

• Experience with modern CI/CD platforms (e.g., Tekton/Spinnaker/Argo CD/Flux) and progressive delivery.

• Prior work with Backstage or other IDPs; plugin development and service catalog design.

• Background in developer analytics and productivity research; familiarity with DORA, DX frameworks

• Experience with remote dev environments (e.g., DevPods/Codespaces-style) at scale.

• Experience with microservices architecture and related DevOps practices.

• Lead time for changes trends down; deployment frequency trends up without increasing risk.

• CI stability & speed improve (p95 build/test time, flake rate, queueing).

• Change failure rate & MTTR drop via safer releases and better rollback automation.

• Developer NPS/DevEx survey and onboarding time improve; IDP adoption grows. (Benchmarked using DORA-style measures.)

What You Will Accomplish:

• Build large-scale applications, low-latency APIs, data pipelines, and foundational architectures to support eBay’s business operations and customer experiences.
• Design and implement highly configurable, metadata-driven platforms to enable seamless ingestion of attributes, rules, models, policies, and derived aggregates.
• Develop machine learning models and Gen AI tools to generate insights and improve customer experiences across eBay.
• Partner with architects, business leaders, and industry experts to devise strategies and scalable solutions.
• Be responsible for the entire software lifecycle, including design, development, testing, and experimentation.
• Mentor and lead junior team members by setting examples and guiding them toward success.

What You Will Bring:

• Prefer Technical degree with 3-5+ years of relevant software development experience.
• Strong hands on Machine Leaning experience, AI/ML/Gen AI, LLM's and proven experience in building and running AI/ML/GenAI models in production environments.
• Outstanding programming skills in Java, Scala, and Python, with hands-on experience in frameworks like PyTorch and TensorFlow.
• Proven experience with APIs and Distributed Systems, building and consuming horizontally scalable RESTful APIs, GraphQL, and distributed systems.
• Hands-on experience with technologies like Spark, Flink, and Kafka with practical experience in their use.
• Strong understanding of SQL, NoSQL, and sophisticated data modeling techniques.
• Hands-on experience with the Hadoop ecosystem (HDFS, MapReduce, Hive, Spark) for building and optimizing large-scale data solutions.

What Will You Do

We are looking for exceptional Engineers, who take pride in creating simple solutions to apparently-complex problems. Our Engineering tasks typically involve at least one of the following:

• Building a pipeline that processes up to billions of items, frequently employing ML models on these datasets

• Creating services that provide Search or other Information Retrieval capabilities at low latency on datasets of hundreds of millions of items

• Crafting sound API design and driving integration between our Data layers and Customer-facing applications and components

• Designing and running A/B tests in Production experiences in order to vet and measure the impact of any new or improved functionality

eBay is an amazing company to work for. Being on the team, you can expect to benefit from:

• A competitive salary - including stock grants and a yearly bonus

• A healthy work culture that promotes business impact and at the same time highly values your personal well-being

• Being part of a force for good in this world - eBay truly cares about its employees, its customers, and the world’s population, and takes every opportunity to make this clearly apparent

Job Responsibilities

• Design, deliver, and maintain significant features in data pipelines, ML processing, and / or service infrastructure

• Optimize software performance to achieve the required throughput and / or latency

• Work with your manager, peers, and Product Managers to scope projects and features

• Come up with a sound technical strategy, taking into consideration the project goals, timelines, and expected impact

• Take point on some cross-team efforts, taking ownership of a business problem and ensuring the different teams are in sync and working towards a coherent technical solution

• Take active part in knowledge sharing across the organization - both teaching and learning from others

Minimum Qualifications

• Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field with 6+ years of relevant industry experience, including 3+ years in people management.

• Proven experience leading machine learning teams in an applied industrial setting.

• Deep understanding of modern ML approaches including classification, regression, NLP, clustering, deep learning, and/or reinforcement learning.

• Strong programming background in Python, Java, or similar, with exposure to production-grade ML systems.

• Proficiency with big data processing frameworks such as Hadoop, Spark, and SQL.

• Excellent communication, storytelling, and stakeholder management skills.

• Demonstrated ability to translate business needs into scientific problems and to prioritize for impact.
  

Additional Qualifications

• Master’s or Ph.D. in a relevant field (Computer Science, ML, Stats, etc.)

• Track record of impactful publications and/or patents in machine learning or related areas.

• Contributions to open-source ML tools or frameworks.

• Experience with modern large language models, graph-based ML, or knowledge graph construction.

• Strong presence in scientific communities through talks, panels, or organizing roles.

• Design and build machine learning models to detect fraud, bot attacks, collusion etc.

• Perform feature engineering, model development, evaluation, and optimization for high-accuracy ML applications.

• Fine-tune and implement Deep Neural Network (DNN) architectures.

• Construct robust ML pipelines for training, validation, and deployment using modern ML stacks.

• Apply prompt engineering techniques with Generative AI models (LLMs, diffusion models, etc.) to tackle application-driven problems.

• Leverage vector databases and build/optimize embeddings for search, retrieval, and semantic understanding.

• Lead efforts in simulation, synthetic data generation, and experimentation.

• Build reliable APIs and services that expose ML model outputs for real-time decisioning.

• Evaluate bias and fairness across population subgroups.

• Maintain logging, tracing, and alerting for model inputs/outputs, feature importance, versions, and pipeline steps.

• Lead and participate in data validation, preprocessing, and cleansing workflows to ensure ML readiness.

• Work closely with engineers, product managers, and collaborators to develop scalable ML-powered applications.
  

What will you bring?

• At least 5 years of experience in building AI/ML-based products and solutions in production environments.

• A solid foundation in Data Structures, Algorithms, Object-Oriented Programming, Software Design, and core Statistics knowledge

• Proven expertise in Python and ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch, Keras.

• Deep understanding of machine learning fundamentals, algorithms, and model evaluation techniques.

• Hands-on experience with ML Ops tools and best practices.

• Experience with OCR, NLP, vector search, embeddings, and LLM-based applications.

• Experience in the close examination of data and computation of statistics

• Proficiency in working with large scale data in hadoop and spark.

• Proficient with prediction accuracy, latency, throughput, confidence scores, and drift (data & concept).

• Strong programming, system design, and debugging skills.

• Experience working in domains such as fraud detection, credit risk, compliance, advertising, or recommendations is highly preferred.

• Publication of research papers or technical articles in ML conferences or journals is highly desirable.

Role Overview:

Primary Job Responsibilities:

• Build close partnership with business teams to Innovate, identify and explore high-impact opportunities for AI and automation, designing innovative solutions that transform processes and enhance decision-making capabilities.
• Lead a team of 7-10 data scientists and data analysts
• Manage end-to-end development and deployment of automation solutions using machine learning techniques, AI algorithms, core Python, and other relevant technologies to solve complex tax-related challenges.
• Analyze large, diverse data sets leveraging SQL, Python, ML algorithms, and automation tools to extract insights, and build scalable automation frameworks
• Exhibit curiosity and proactiveness to stay up to date with AI tools and implementation of those tools in business process automations
• Continuously monitor, optimize, and scale AI and automation solutions, ensuring they remain efficient, reliable, and aligned with evolving business needs.
• Foster a culture of self-serve analytics across the organization.

Job skills required:

• Intellectual curiosity, passion for problem-solving, and comfort with ambiguity.
• Proven experience delivering end-to-end AI, machine learning, and automation solutions— from problem scoping, data collection, model development, to production deployment.
• Strong technical skills in data analysis and automation using SQL and Python;
• Experienced in handling big data (Hadoop, Teradata, etc.) and agile experience
• Ability to translate business needs into scalable, maintainable software and automation solutions.
• Capable of working as an individual contributor while collaborating effectively within a global team as well as managing a team of data scientists.
• Sound communication and interpersonal skills to effectively manage projects and influence cross- functional teams.

Desired Qualifications:

• 10+ years of experience delivering advanced AI, machine learning, and automation solutions in complex business environments.
• Strong programming proficiency in Python and SQL

Shape the Future of AI-Driven eCommerce Discovery

You’ll join the org and play a key role in designing the backbone of next-gen search, recommendations, and generative AI experiences.

What You’ll Work On

• Transform Product Data into Insights
  Conduct deep-dive SQL and Python analyses to uncover opportunities in taxonomy, ontology, and catalog structure that enhance discovery and user experience.

• Harness the Power of Generative AI
  Use prompt engineering and LLMs to create innovative tools for classification, taxonomy validation, and data enrichment.

• Build & Evaluate AI/ML Models
  Design frameworks to evaluate product knowledge models, semantic embeddings, and ML-based categorization systems.

• Drive Data-Informed Strategy
  Translate complex findings into clear, actionable insights for Product and Engineering teams. Influence roadmap decisions on entity resolution, catalog optimization, and knowledge graph development.

• Partner Across Functions
  Collaborate closely with Applied Research, Engineering, and Product teams to build and deploy high-impact data and AI solutions at scale.

• Experiment & Innovate Fast
  Prototype quickly, validate hypotheses, and iterate on structured data and AI-driven solutions that push boundaries.

What You Bring

• 12+ years of experience in data science or analytics roles, including 5+ years leading teams

• Proven track record building data products, knowledge graphs, and scalable data pipelines

• Deep understanding of eCommerce search, recommendation systems, and product analytics

• Hands-on experience with LLMs, prompt engineering, and RAG techniques (preferred)

• Strong communication skills and ability to influence cross-functional stakeholders

• Experience evaluating ML models with custom metrics and robust frameworks

• Startup mindset—comfortable with ambiguity, bias for action, and fast iteration

Why Join Us

• Be at the forefront of AI-powered product discovery in eCommerce

• Own high-impact initiatives in a startup-style culture with real autonomy

• Work alongside world-class talent across AI, Product, and Engineering

• Build solutions that scale—serving millions of users and shaping the future of shopping

Ready to lead the next wave of AI + Data innovation in commerce? Let’s build the future together.

• Lead Strategic Transformation: Spearhead the design, development, and evolution of eBay's Cloud Software-Defined Platforms, Infrastructure, and Networking, ensuring our private cloud compute environment is at the cutting edge of performance and scalability.

• Drive Operational Excellence with AI: Champion our Site Reliability Engineering (SRE) principles, leveraging advanced AI/ML techniques to identify new opportunities for global operational efficiency and predictive intelligence across our vast infrastructure.

• Build & Inspire World-Class Teams: Recruit, mentor, and lead a diverse, globally distributed team of infrastructure software engineers. Foster a culture of technical excellence, continuous learning, and innovation, empowering your team members to achieve their full potential and grow their careers.

• Influence & Execute: Translate high-level business needs into clear, actionable engineering plans. Provide expert technical guidance and leadership, automating processes and enhancing team productivity from ideation through deployment and operations.

• Ensure End-to-End Quality: Own the full software lifecycle instrumentation, from initial requirements gathering to robust software development and seamless deployment, ensuring quality, observability, and scalability are built-in from day one.

• Strategic Collaboration:

• 15+ years of progressive industry experience with a deep focus on large-scale infrastructure, distributed systems, and/or cloud engineering.

• 10+ years in senior leadership roles within the technology sector, ideally managing global, geographically distributed software development and operations teams.

• Proven expertise in Software-Defined Infrastructure and Software-Defined Networking.

• Demonstrated experience in Site Reliability Engineering (SRE) and building highly resilient, scalable systems.

• Experience leveraging AI/ML to drive operational insights, productivity, automation, or efficiency improvements in infrastructure.

• Exceptional ability to lead organizational change management, influence executive stakeholders, and drive consensus in complex, cross-functional environments.

• Expertise in modern global software development methodologies (e.g., Agile, DevOps).

• Superior communication skills , with a track record of clearly articulating critical technical updates and strategies to diverse audiences, including C-level leadership.

• Proficiency in infrastructure as code (IaC) and traffic engineering .

• Hands-on experience with Kubernetes and related container orchestration technologies.

• Experience with service mesh implementations .

• Leadership in open-source projects related to cloud infrastructure.

• Strong understanding of networking, cybersecurity principles, and related fields within a cloud context.

• Experience operating and scaling platforms in high-traffic, global, and exceptionally large-scale environments.

Familiarity with multiple programming languages, including