Principal Engineer, Agentic Engineering

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Reports to:

Chief Technology Officer

The Opportunity

Every engineering organisation is adopting AI copilots. That is table stakes. What separates the best from the rest is whether AI is a tool on a developer's laptop or a systematic participant in how the organisation delivers software.

At Bullish, we have chosen the latter. Our north star is a fully autonomous development workflow where engineers focus on what matters most: specifications, testing harnesses, and validation — while AI agents handle the predictable work. The foundational systems are already in production. We need someone to lead this forward.

As Principal Engineer, you will be the technical authority for AI and agentic engineering across Bullish. You will shape the architecture, build the systems, and drive the organisational shift from AI-assisted to AI-native software delivery.

The Role

This is a hands-on technical leadership role. You will:

• Build the agent infrastructure that lets AI agents discover each other, communicate, and coordinate — so any team can deploy an agent and it joins the ecosystem

• Evolve our autonomous coding pipeline — task in, pull request out, with deterministic multi-agent execution, full cost control, and human review before merge

• Make engineering standards executable — encoding conventions as AI behaviours that activate in developer workflows, not documents pinned to a wiki

• Transform the delivery pipeline — auditing every manual gate and either automating it, replacing it with an agent, or justifying its retention as a deliberate human decision point

• Own AI infrastructure end to end — model routing, LLM proxy, cost attribution, evaluation frameworks, and observability for production AI systems

What You’ll Do

• Set the technical direction for AI and agentic systems across the engineering organisation

• Design and build production systems: agent orchestration, autonomous coding pipelines, LLMOps infrastructure

• Stay hands-on: write code, review PRs, debug production issues, and set the technical bar

• Evaluate new models, frameworks, and techniques as the landscape evolves — and bring what works into the organisation

• Establish metrics and observability for agent output quality, cost, and throughput

• Recruit and mentor engineers as the function grows, while remaining a primary contributor yourself

• Partner with the AI Enablement team to provide the technical foundation for business team AI adoption

What You’ll Bring

• 8+ years of engineering experience, including significant recent work with LLM and agent systems

• Hands-on experience building with LLM APIs (Anthropic, Ope