Overview: Job Purpose
Intercontinental Exchange (ICE) is seeking a Lead AI/GenAI Engineer responsible for architecting and delivering intelligent systems that accelerate software engineering workflows and unlock new capabilities across the organization. This role sits at the intersection of applied AI and platform engineering, building production-grade agentic systems, knowledge pipelines, and retrieval-augmented solutions that directly improve developer productivity, quality, and throughput. The ideal candidate brings deep hands-on experience shipping GenAI systems at enterprise scale (not just prototypes) and can move fluidly between designing technical architecture and influencing business strategy. Passion for applying AI to real engineering problems, strong analytical judgment, and the ability to operate with autonomy are essential to success in this role.
Responsibilities
- Architect and implement AI systems end-to-end, including knowledge pipelines, AI agents, and retrieval-augmented solutions, from prototype to production deployment.
- Advocate for AI usage and adoption within the organization, applying best practices and staying current with emerging solutions and related technologies.
- Stand up scalable data pipelines for ingestion, preprocessing, embedding generation, and continuous model training/retraining.
- Lead agentic SDLC automation, starting with requirements capture, refinement, and validation, then expanding progressively into design, development, testing, and deployment.
- Partner with engineering, QA, and business stakeholders to identify the highest-leverage automation opportunities.
- Define and track impact metrics (cycle time, quality, throughput) to measure real outcomes, not adoption theater.
- Champion best practices in CI/CD, evaluation, observability, and responsible AI as first-class engineering disciplines.
Knowledge and Experience
- 10+ years of hands-on software engineering, with a track record of shipping and maintaining production systems at enterprise scale.
- Demonstrated experience architecting and delivering GenAI systems in production, including agent authoring, prompt orchestration, and evaluation frameworks (real production systems, not POCs).
- Strong grounding in MLOps, model serving, monitoring, evaluation, and CI/CD for AI systems.
- Fluency across the modern AI stack: LLMs, vector databases, embeddings, agent frameworks, and fine-tuning workflows.
- Ability to translate ambiguous, cross-functional problems into concrete technical roadmaps and ship against them.
- Strong product instincts: able to decide what's worth building, defend trade-offs to non-technical stakeholders, and move comfortably between code and customer.
Preferred Knowledge and Experience
- Prior team leadership or engineering management experience (this role can evolve into a management track for the right person).
- Experience applying AI to SDLC tooling specifically: requirements engineering, code generation, testing automation, developer productivity.
- Ability to implement GraphRAG-style pipelines that combine vector databases and knowledge graphs to ground AI outputs in verifiable, traceable facts.
- Working experience with knowledge graphs (Neo4j or similar) and graph data modeling for enterprise data.
- Open-source contributions in AI/ML, graph, or developer-tooling ecosystems.
- Familiarity with observability tooling such as OpenTelemetry and MLFlow.
- Experience with LLM fine-tuning (open-source or proprietary) and optimization for performance, latency, and cost.
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-: Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.