Job Purpose

Intercontinental Exchange (ICE) is seeking a Lead 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 similar solutions that directly improve developer productivity, quality, and throughput.

The ideal candidate brings hands-on experience shipping GenAI systems at scale 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

• Lead engineering projects working in TypeScript/JavaScript and/or Rust.
• Architect and ship complete systems, from first prototype through to production.
• Lead agentic SDLC automation, working closely with engineering, QA, and business stakeholders to figure out where automation pays off most and build out solutions.
• Set engineering standards for how we build with and without agents, including evaluations, guardrails, and deployment patterns.
• Evaluate new tools and techniques and mentor developers in advanced concepts.
• Engage with development teams to identify opportunities for process improvement.

Knowledge and Experience

• Bachelor’s Degree or equivalent in Computer Science or related field.
• 8+ years of senior software engineering experience, with production systems you've shipped and supported at scale.
• Comfort across the current AI stack, including LLMs, vector databases, embeddings, agent frameworks, and fine-tuning.
• The ability to take a rough, cross-functional problem, turn it into a concrete plan, and then deliver it.
• GenAI systems you've taken to production, including agent authoring, prompt orchestration, and evaluation frameworks running against real traffic.
• Good product sense. You can pick what's worth building, explain a trade-off to someone non-technical, and move between the code and the people using it.

Preferred Knowledge and Experience

• Knowledge Base / Knowledge Graph experience, both using and implementing
• AI applied to SDLC tooling: requirements engineering, code generation, test automation, developer productivity.
• Observability tooling like OpenTelemetry / MLflow, and experience fine-tuning or otherwise tuning LLMs for latency and cost.
• Open-source work in the AI/ML, graph, or developer-tooling worlds.
• A background in financial services or fintech, or familiarity with equity and commodity derivatives.
• Some team leadership or engineering management experience.

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