Engineer Lead, Artificial Intelligence / Machine Learning (GitHub copilot)

Are you curious, motivated, and forward-thinking? At FIS you’ll have the opportunity to work on some of the most challenging and relevant issues in financial services and technology. Our talented people empower us, and we believe in being part of a team that is open, collaborative, entrepreneurial, passionate and above all fun.

About the team

The Client Office Custom Development CoE team is a horizontal Center of Excellence for the Client Office, helping drive revenue growth and deliver significant cost savings by identifying, designing, and implementing GenAI and Agentic AI solutions at enterprise scale.

The Client Office is one of the three major verticals at FIS, supporting a wide range of products and solutions across funds management, cleared derivatives, commercial lending, corporate treasury, insurance risk, electronic trading, RegTech, wealth, and retirement.

The team is composed of highly motivated Product Engineers, Functional SME’s, QA’s, Architects, GitHub copilot experts focused on embedding AI into real-world delivery workflows.

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 hands-on adoption of AI-assisted engineering, establish prompt and agent standards, and embed responsible AI practices into day-to-day 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 agent-based systems, including planning, memory, tool usage, and orchestration
• Hands-on experience implementing agentic workflows, including:
• Multi-agent collaboration
• Human-in-the-loop systems
• Semi-autonomous 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 systems -including autonomous decision-making, 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:
  • scikit-learn
  • TensorFlow
  • PyTorch
  • Keras
  • pandas
• Hands-on experience building RESTful APIs using Flask or FastAPI

Nice to Have

• Experience with LLM fine-tuning, parameter-efficient tuning (LoRA/QLoRA)
• Working knowledge of production-grade 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

Bachelor’s 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

What we offer you

• A multifaceted job with a high degree of responsibility and a broad spectrum of opportunities
• A broad range of professional education and personal development possibilities - FIS is your final career step!
• A competitive salary and benefits
• A variety of career development tools, resources and opportunities

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Sourcing Model

Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.