Among computer and information research scientists, AI is already used for a large share of the tasks. Measured exposure for computer and information research scientists: 34% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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Python

About the job

About Us:

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

What We’re Looking For

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

Nice to Have

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