Engineer Lead, Artificial Intelligence / Machine Learning (GitHub)
- Fiserv
- 8 - 13 years
- Pune
- 24 days ago
- Email to a friend
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Job Description
Engineer Lead, Artificial Intelligence / Machine Learning (GitHub copilot)
What you will be doing
As an Artificial Intelligence / Machine Learning Engineer Lead, you will play a pivotal role in driving the enterprise rollout of GitHub Copilot across the Services organization and building AI agents and agentic workflows that accelerate software delivery.
You will work closely with development, QA, and technical consulting teams to enable handson adoption of AIassisted engineering, establish prompt and agent standards, and embed responsible AI practices into daytoday delivery
What you bring:
Knowledge / Experience
- 8+ years of overall experience, with 4+ years working on AI / GenAI / Agentic AI
- Experience designing and building applications using GitHub copilot
- Experience in driving GitHub adoption across enterprise
- Experience in prompt engineering
- Proven experience building agentbased systems, including planning, memory, tool usage, and orchestration
- Handson experience implementing agentic workflows, including:
- Multiagent collaboration
- Humanintheloop systems
- Semiautonomous task execution
- Experience integrating AI systems with enterprise platforms, APIs, repositories, and workflows
- Strong experience evaluating model, agent, and system behavior for accuracy, reliability, grounding, and safety
- Experience with vector databases and retrieval systems, including RAG and hybrid retrieval patterns
- Experience building and deploying REST services using Flask or FastAPI
- Experience working with cloud platforms (Azure, AWS, or GCP) and AI/ML studios
Skills
- Strong hands-on experience with Large Language Models (LLMs) and GitHub copilot.
- Familiarity with LangChain, Langgraph,LlamaIndex, Autogen, or OpenAI Assistants API
- Strong proficiency in Python.
- Deep understanding of Agents Agentic AI systemsincluding autonomous decisionmaking, tool/function calling, planning, and orchestration.
- Proficiency with prompting techniques, structured outputs, model routing, and context/memory management.
- Understanding of different model types:
- Proprietary (e.g., GPT-class)
- Open-weight models
- Embedding models
- Multimodal models
- Understanding of AI orchestration frameworks (conceptual level acceptable)
- Knowledge of model access and orchestration protocols such as Model Context Protocol (MCP) or similar abstraction layers
- Ability to design systems that:
- Switch models
- Route prompts
- Manage context, memory, and toolchains
- Experience evaluating GenAI systems (hallucinations, grounding, safety)
- Experience with ML/AI frameworks such as:
- scikitlearn
- TensorFlow
- PyTorch
- Keras
- pandas
- Hands-on experience building RESTful APIs using Flask or FastAPI
Nice to Have
- Experience with LLM finetuning, parameterefficient tuning (LoRA/QLoRA)
- Working knowledge of productiongrade MLOps (CI/CD, monitoring, observability)
- Experience with vector DBs like Pinecone, Chroma, Redis, Weaviate, or Milvus
- Understanding of security, compliance, and data governance for GenAI systems
Qualifications
Bachelors degree in engineering or related field or the equivalent combination of education, training, or work experience
Competencies
- Fluent in English
- Excellent communicator ability to discuss technical and commercial solutions to internal and external parties and adapt depending on the technical or business focus of the discussion.
- Attention to detail track record of authoring high quality documentation.
- Organized approach manage and adapt priorities according to client and internal requirements.
- Self-starter but team mindset - work autonomously and as part of a global team
Job Classification
Industry: BPM / BPOFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Solution ArchitectEmployement Type: Full timeContact Details:
Company: FISLocation(s): Pune
Keyskills: github python restful ai machine learning llm artificial intelligence redis pandas tensorflow restful apis pytorch keras flask
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