Staff AI Agent Engineer

Liberate builds AI agents to automate manual tasks for the $2.7T insurance industry. We started with voice — the hardest and most valuable channel in insurance — and are now expanding into full workflow automation across sales, servicing, and claims. Our long-term vision is to build reasoning agents capable of handling the entire spectrum of insurance carrier and broker operations. We've raised $72M to date, including a $50M Series B in October 2025, backed by top-tier venture firms.

Location: Boston or San Francisco (Berkeley), hybrid (2 days/week in office)

About The Role

As a Staff AI Agent Engineer, you are a force multiplier for customer deployments and agent quality. You own complex customer launches end to end and turn hard, bespoke problems into repeatable patterns. You operate with strong judgment, raise the engineering bar in the work, and reduce dependency on leadership by owning outcomes directly.

This role is hands-on, customer-facing, and deeply technical. You are not a solutions engineer. You are an engineer who ships.

What You’ll Do

• Own complex, high-impact agent deployments from design through production
• Design, build, and iterate on agent workflows, prompts, evals, and integrations
• Turn customer-specific learnings into reusable templates, playbooks, and patterns
• Partner with Product and Platform to influence roadmap based on real-world usage
• Debug and improve agent behavior using structured evals, monitoring, and analysis
• Lead technical reviews for agent design, launch readiness, and post-launch quality
• Mentor other Agent Engineers through example and direct coaching
• Raise the bar on engineering quality, operational rigor, and reuse in deployments

Must Have

• 6+ years of professional software engineering experience
• Strong hands-on experience building and operating production systems
• Fluency in Python and modern backend systems (APIs, services, cloud)
• Experience working with LLM-based systems, prompts, tools, or agent frameworks
• Ability to reason about quality, failure modes, and operational risk
• Comfort working directly with customers on technically complex problems
• High ownership, good judgment, and the ability to operate under pressure

• Experience with agentic systems, eval frameworks, or AI observability
• Prior work in B2B SaaS, enterprise software, or regulated environments
• Experience turning bespoke solutions into reusable systems