3 days ago
Responsibilities
- Drive the enterprise rollout and adoption of GitHub Copilot across the Services organization.
- Design and build AI agents and agentic workflows that accelerate software delivery.
- Establish prompt, agent, and responsible AI standards and embed them into delivery workflows.
- Implement multi-agent collaboration, human-in-the-loop systems, and semi-autonomous task execution.
- Integrate AI systems with enterprise platforms, APIs, repositories, and workflows.
- Evaluate model, agent, and system behavior for accuracy, reliability, grounding, hallucinations, and safety.
- Work with development, QA, and technical consulting teams to enable hands-on AI-assisted engineering adoption.
- Build and deploy RESTful services using Flask or FastAPI.
Requirements
- 8+ years of overall experience, including 4+ years working with AI, GenAI, or agentic AI.
- Experience designing and building applications using GitHub Copilot and driving GitHub adoption across an enterprise.
- Experience with prompt engineering, agent-based systems, planning, memory, tool usage, orchestration, and agentic workflows.
- Experience integrating AI systems with enterprise platforms, APIs, repositories, and workflows.
- Experience with vector databases, retrieval systems, RAG, and hybrid retrieval patterns.
- Strong hands-on experience with LLMs, GitHub Copilot, Python, prompting techniques, structured outputs, model routing, and context or memory management.
- Familiarity with LangChain, LangGraph, LlamaIndex, AutoGen, or the OpenAI Assistants API.
- Knowledge of proprietary, open-weight, embedding, and multimodal models, AI orchestration frameworks, and Model Context Protocol or similar abstraction layers.
- Experience with Azure, AWS, or GCP and AI/ML studios.
- Experience with scikit-learn, TensorFlow, PyTorch, Keras, or pandas.
- Bachelor’s degree in engineering or a related field, or an equivalent combination of education, training, or work experience.
- Preferred qualifications include LLM fine-tuning, LoRA or QLoRA, production-grade MLOps, vector databases such as Pinecone, Chroma, Redis, Weaviate, or Milvus, and knowledge of security, compliance, and data governance for GenAI systems.
- Fluent English communication, strong technical documentation ability, organization, adaptability, and the ability to work autonomously and collaboratively are required.
Benefits
- Full-time position with a high degree of responsibility and broad opportunities.
- Professional education, personal development, and career development tools and resources.
- Competitive salary and benefits.
- Opportunity to work with a global, collaborative team across financial services and technology.
Tech Stack
Categories
About FIS
Unlocking financial technology. Bringing the world’s money into harmony. At FIS, we advance the way the world pays, banks, and invests. With decades of expertise, we provide financial technology solutions to financial institutions, businesses, and developers. Headquartered in Jacksonville, Florida, we’re a proud member of the Fortune 500® and the Standard & Poor’s 500® Index. Let's innovate together.