Full-Time AI Engineer

• Rapidly prototype AI agents and guided workflows that solve concrete customer problems; ship thin slices, instrument, and iterate with real usage.
• Design and implement cloud-native backend services that orchestrate prompts, tools, retrieval, and automations; own the path from POC to production.
• Build robust retrieval for LLMs (search/vector pipelines, context assembly, tool selection) in partnership with data engineering.
• Establish evaluation loops: offline/online tests, golden sets, regression checks, and human-in-the-loop review to measurably improve quality and safety.
• Contribute to developer experience: reusable agents/tools, SDKs, templates, and internal documentation that speed up future builds.
• Collaborate with customers and internal stakeholders to frame problems, define success metrics, and translate insights into productizable solutions.
• Lead design discussions and code reviews; mentor teammates and raise the quality bar while keeping momentum high.

• 4–8+ years as a software/AI engineer, including shipping 0→1 products or features in startup-like environments.
• Strong in Python (and comfortable with TypeScript); able to build production services and integrate with external systems/APIs.
• Proven experience taking LLM/agent systems to production (tool use, function calling, planning/exec, retrieval-augmented generation).
• Hands-on with evaluation (offline/online), prompt engineering, tracing, and observability for AI systems.
• Familiarity with vector databases/search, embeddings, and context/retrieval patterns; pragmatism about when/what to index.
• Solid backend fundamentals (services, queues, data models, CI/CD, cloud) and a bias to automate what you repeat.
• Excellent communication and product sense—able to turn fuzzy business problems into clear technical plans and measurable outcomes.
• Fast mover: comfort with ambiguity, crisp prioritization, and the judgment to ship small, safe increments quickly.
• Nice-to-have: open-source contributions, hackathon wins, or a portfolio of shipped side projects; experience at both an early-stage startup and a larger-scale system.

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