Principal Engineer, Agentic Engineering

Bullish • New York, NY

2d • $200,000 - $325,000

About The Position

About Bullish Bullish is an institutionally focused global digital asset platform that provides market infrastructure and information services. These include: Bullish Exchange – a regulated and institutionally focused digital assets spot and derivatives exchange, integrating a high-performance central limit order book matching engine with automated market making to provide deep and predictable liquidity. Bullish Exchange is regulated in Germany, Hong Kong, and Gibraltar. CoinDesk Indices – a collection of tradable proprietary and single-asset benchmarks and indices that track the performance of digital assets for global institutions in the digital assets and traditional finance industries. CoinDesk Data - a broad suite of digital assets market data and analytics, providing real-time insights into prices, trends, and market dynamics. CoinDesk Insights – a digital asset media and events provider and operator of Coindesk.com, a digital media platform that covers news and insights about digital assets, the underlying markets, policy, and blockchain technology. 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

Requirements

• 8+ years of engineering experience, including significant recent work with LLM and agent systems
• Hands-on experience building with LLM APIs (Anthropic, OpenAI, Google) and agent frameworks (LangChain, LlamaIndex, or similar)
• Direct experience designing and building agentic workflows or multi-agent systems — not just using copilots, but building the infrastructure behind them
• Mastery of backend development, distributed systems, and Python
• Strong LLMOps skills: CI/CD for AI systems, production observability, cost attribution, and spend control
• Experience deploying AI coding agents or developer tools to engineering teams
• Ability to influence technical direction across an organisation and build consensus for architectural decisions

Nice To Haves

• Experience in digital assets, blockchain, or traditional financial services
• Experience fine-tuning and deploying open-source LLMs in production
• Experience with data privacy and security compliance in a regulated environment

Responsibilities

• 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 This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed
• Number of Employees: 101-250 employees