AI Agent Engineer
Engineers in this role design and deploy autonomous AI agents that solve real-world business problems across diverse industries, from finance and healthcare to infrastructure and marketing operations. They move fast across the full development lifecycle—from prototyping with frontier LLMs to shipping production systems that handle complex customer interactions, workflow automation, and operational decision-making at scale. What sets this work apart is the emphasis on reliability and observability: these engineers don't just build agents, they ensure they perform consistently in ambiguous, high-stakes environments while integrating with enterprise systems and human operators. Typically embedded in dedicated agent or agentic AI teams within product-focused AI companies, these roles sit at the intersection of platform engineering and direct impact, partnering closely with product managers, domain experts, and cross-functional stakeholders to turn loosely defined opportunities into robust, measurable business outcomes.
Skills
What companies are looking for in this role.
Designing and building end-to-end agentic AI systems that execute autonomous workflows and multi-step tasks
Developing scalable distributed systems and backend infrastructure for agent runtime execution and orchestration
Orchestrating multi-agent systems with tool use, planning, and decision-making capabilities
Integrating large language models and AI agents with external APIs, databases, and tool ecosystems
Designing and implementing evaluation frameworks, guardrails, and feedback loops for production agent systems
Integrating agents with domain-specific tools and enterprise software systems
Operating systems at scale with focus on reliability and fault tolerance mechanisms
Optimizing agent systems for latency, reliability, cost efficiency, and production correctness
Building observability, monitoring, and diagnostic systems for agent behavior and performance
Implementing retrieval-augmented generation pipelines and knowledge integration systems for AI agents
Building agent memory systems, state management, and context handling mechanisms
Implementing sandboxing, isolation, and secure execution environments for autonomous agent operations
Debugging complex systems spanning model behavior, inference stacks, and harness execution
Implementing control-plane logic for agent routing, planning, and tool invocation with safety guarantees
Developing prompt engineering strategies and model selection approaches for agentic workflows
Building automated workflow systems that encode structured processes as agent-executable steps
Implementing agentic coding practices using AI-assisted development tools and platforms
Designing experimentation frameworks and A/B testing systems for agent behavior optimization
Building voice and real-time agent systems including transcription and turn-taking
Owning agent projects end-to-end from initial design through production deployment and iteration
Collaborating cross-functionally with product managers, researchers, and domain experts to shape agent capabilities
Translating complex business requirements and use cases into reliable agent implementations
Building production-grade components and reusable abstractions from early-stage prototypes
Conducting user research and gathering requirements from direct customer and stakeholder engagement
Identifying high-impact use cases and prioritizing automation initiatives across customer lifecycles
Technology
The tools and technologies that define this role.
Open Jobs
109 open AI Agent Engineer jobs across 36 companies.
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