Software Engineer, Applied AI
$170,000–$300,000 year
RemoteUnited States
Job Summary
Design and iterate on agent behavior across real go-to-market workflows, mapping manual processes into reliable, steerable agent-driven flows. Build core agent infrastructure including memory systems, tool architectures, and retrieval frameworks to support production execution. Develop and run evals measuring task completion and robustness, analyzing real failures to improve system reliability. Work with product to transition agent features from prototype through general availability, ensuring agents are dependable enough to run unattended. This role sits at the intersection of agent products and the shared platform, focusing on closing the gap between demo capabilities and production dependability.
Required Qualifications
- Experience building or shipping production systems with LLMs or agents — not just prototyping
- Strong backend fundamentals — APIs, databases, distributed systems
- Experience with model or agent evaluation: designing evals, measuring regressions, or turning fuzzy quality questions into measurable signals
- A systems-and-outcomes mindset — you care about whether the product actually works for users, not just about model metrics in isolation
- Comfort debugging messy, real-world failures and a bias toward shipping and iterating quickly in a space where best practices are still being figured out
Desired Qualifications
- Experience with agent frameworks, tool-calling systems, or retrieval architectures (vector search, hybrid search, RAG)
- Experience building or maintaining eval/benchmark infrastructure for LLM-based systems, or running fine-tuning in production
- Experience with GTM, sales, or marketing workflows (e.g. lead sourcing, enrichment, audience building)
- Familiarity with Clay's stack: React, TypeScript, Python, AWS (Aurora/Postgres, ECS/Fargate, Lambda, OpenSearch, Elasticache/Redis), Terraform, Datadog
- A growth mindset — we're building a team that's curious, open-minded, and happy to invest in each other's learning, not just their own
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