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Strong employer brand, hybrid work, and mid-level seniority amplify applicant competition.
Specialized agentic LLM, eval, and enterprise integration skills are highly domain-specific and less transferable.
Explicit LLM/agent experience, eval design, and language plus platform skills create strict technical filters.
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Design, build, and maintain production LLM-powered AI agents that automate software delivery lifecycle tasks including intake, coding, testing, release, and monitoring.
Develop and maintain evaluation suites, guardrails, and human-in-the-loop approval mechanisms to ensure agent output quality and trustworthy autonomous operations.
Contribute to and improve the underlying AI platform, including orchestration, security, integrations, and observability, with focus on reliability, scalability, and cost efficiency.
3+ years of professional software engineering experience with a track record of delivering and operating production systems.
Hands-on experience building LLM-powered applications or agents, including prompt/context engineering and multi-agent workflows.
Strong proficiency in Python or TypeScript and familiarity with API, microservices, event-driven architecture, CI/CD, automated testing, and cloud platforms.
Experience designing automated evaluations for AI systems or strong test engineering skills applicable to non-deterministic software.
Experienced in architecting and shipping LLM-powered agents and AI orchestration systems at scale within large or complex technical environments.
Comfortable designing and enforcing evaluation and governance standards to build trust in AI autonomy in enterprise delivery settings.
Strong engineering craftsmanship with focus on platform reliability, scalability, secure enterprise integrations, and clear communication for cross-functional impact.