AI Engineer (Agents)

• Production-Grade Agent Architecture: Architect, develop, and maintain scalable, stateful AI agents. You won't just build "demos"; you will ship hardened systems using Python and modern frameworks (Google ADK, LangGraph, CrewAI, etc.) that handle real-world edge cases.
• LLMOps & Observability: Establish production monitoring for agentic workflows. Implement tracing and observability (e.g., LangSmith, Arize Phoenix, or Weights & Biases) to track reasoning paths, tool-calling success rates, and latency bottlenecks.
• End-to-End Production Integration: Lead the integration of AI agents into core product infrastructure (Payments, Fraud, etc.). Own the full lifecycle, from containerization (Docker/Kubernetes) to CI/CD deployment and post-launch stability.
• Advanced Evaluation Pipelines: Move beyond basic metrics. Design automated "evals-as-code" using LLM-as-a-judge, semantic similarity testing, and adversarial benchmarking to ensure agent safety and groundedness before every release.
• Performance & Cost Engineering: Optimize RAG pipelines and agent loops for production constraints. Implement caching strategies, prompt compression, and model routing to balance inference costs with high-performance requirements.
• Technical Leadership: Mentor junior engineers on software craft. Drive best practices in asynchronous programming, error handling for non-deterministic outputs, and structured data validation (Pydantic, etc.).
• Experience : 7+ years of hands-on experience in software engineering, with at least 2 years dedicated to building and deploying production-grade AI/ML applications, specifically focused on Large Language Models (LLMs) or generative AI.
• Technical Mastery : Mandatory expertise in Python and deep familiarity with 1 core LLM APIs and frameworks (OpenAI SDK, Google AI SDK, CrewAI, LangChain, etc.).
• Agentic System Knowledge : Proven experience implementing agentic systems, including knowledge of RAG, vector databases, and memory/state management.
• Engineering Fundamentals : Strong understanding of software development best practices, version control (Git/GitHub), and CI/CD pipelines.

with personal projects or demonstrable contributions on GitHub is a strong plus.

• Execution & Communication : Proven ability to translate high-level business needs into concrete, maintainable, and well-tested code.
• These are the applicable requisites, although equivalent competencies in any of the above will also be considered.
• Mid: $105,000–$170,000 Senior: $160,000–$245,000 Staff: $230,00–$320,000
• Mid: $105,000–$170,000
• Senior: $160,000–$245,000
• Staff: $230,00–$320,000
• Initial stock options grant
• Annual performance bonus
• Health, dental, and vision plans
• Continuous learning opportunities
• Unlimited PTO
• Paid parental leave
• Empowering opportunities for growth in a dynamic entrepreneurial environment