Forward Deployed AI Engineer, Enterprise Agents

About the Company

We are a well-funded AI infrastructure company backed by tier-1 US venture capital firms, building the next generation of enterprise AI agents for highly regulated industries.

Our platform helps large enterprises turn how work actually happens into governed AI execution. Our agents operate across real enterprise software, inside customer-controlled environments, with policy, human authority, and auditability built into every run.

We are working with some of the world’s largest regulated enterprises to bring AI agents out of demos and into production.

The Role

We are looking for a Forward Deployed AI Engineer to help deploy AI agents into complex, high-stakes enterprise environments.

This is a hands-on engineering role at the intersection of applied AI, production software, enterprise workflows, and customer deployment. You will work directly with customer teams to understand mission-critical operational workflows, translate them into agentic systems, deploy those systems in secure production environments, and improve them through evals, instrumentation, and rapid iteration.

This is not a traditional machine learning research role, and it is not traditional solutions engineering. You will be building and deploying production AI agents that operate across real enterprise systems, handle workflow variation, respect policy and permission boundaries, escalate when human authority is required, and leave a defensible execution trail.

You should be excited by ambiguous, high-trust environments where the goal is not a polished demo, but real production impact.

What You’ll Do

Work directly with large enterprise customers to understand complex operational workflows across tools, systems, documents, and teams.

Design, build, and deploy AI agents that can execute approved workflows across enterprise software environments.

Translate messy real-world processes into reliable agentic systems with clear boundaries, escalation points, and evaluation criteria.

Build and improve evals, test harnesses, observability, and debugging tools to measure agent reliability and production readiness.

Partner with product, research, engineering, and customer stakeholders to move workflows from discovery to production.

Debug failures across models, tools, prompts, workflows, permissions, infrastructure, and customer environments.

Help define repeatable deployment patterns for regulated enterprise customers.

Work onsite or embedded with customers when needed.

What We’re Looking For

5+ years of software engineering experience, including experience building or deploying production systems.

2+ years of hands-on experience with AI/ML, LLMs, agents, workflow automation, browser/computer-use agents, or AI systems that interact with software.

Strong software engineering fundamentals.

Strong Python experience. TypeScript, backend engineering, infrastructure, or cloud experience is a plus.

Experience with evals, observability, reliability engineering, tool orchestration, prompt iteration, or model behavior debugging.

Ability to work directly with technical and non-technical customer stakeholders.

Comfort operating in ambiguous environments where workflows are messy, requirements evolve, and the right answer is discovered through iteration.

Strong product sense and a bias toward shipping.

Ability to reason carefully about security, permissions, auditability, data boundaries, and human-in-the-loop controls.

High ownership, low ego, and comfort being close to the customer.

Nice to Have

7+ years of software engineering experience, or prior experience in a senior / staff-level engineering role.

Experience deploying AI, automation, or enterprise software systems in regulated industries such as financial services, insurance, healthcare, or government.

Experience with enterprise security reviews, VPC / private-cloud deployments, SOC 2, SSO, RBAC, audit trails, or data residency requirements.

Background in applied AI research, agents, computer-use agents, browser automation, workflow automation, robotics, or reinforcement learning.

Experience as a forward deployed engineer, solutions architect, founding engineer, implementation engineer, or technical customer lead.

Prior startup experience.

Who You Are

You like being close to the real problem, not just the codebase.

You are comfortable walking into an enterprise environment, understanding how work actually happens, and turning that understanding into software.

You care about reliability, not just model capability.

You can move between customer conversations, systems design, prompt/model debugging, backend engineering, and production deployment.

You want to build AI systems that do real work in the real world.