Staff AI Agent Engineer
Liberate
San Francisco Bay Area · Posted February 12, 2026
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How AI is used in this kind of work
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.
Skills this job asks for
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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