THE OPPORTUNITY

We’re seeking a seasoned Python Architect to lead the design and implementation of our next-generation AI platform. In this role, you will architect robust, scalable solutions that integrate large language models (LLMs), coordinate agentic workflows, and leverage modern NoSQL databases and vector stores for high-performance retrieval. You’ll collaborate closely with product, data science, and DevOps teams to turn cutting-edge AI research into production-ready services.

• Architectural Leadership: Define system architecture and best practices for AI/ML services, ensuring high availability, scalability, and security.
• LLM Integrations: Design and implement integrations with leading LLMs (e.g., OpenAI, Anthropic), including fine-tuning pipelines, prompt orchestration, and inference scaling.
• Agentic Implementations: Lead development of agent-based workflows—using frameworks such as Google’s ADK or LangGraph—to automate multi-step decision processes and dynamic task orchestration.
• Data Layer Design: Architect NoSQL database schemas (e.g., MongoDB, DynamoDB) optimized for semi-structured legal/financial metadata.
• Vector Search: Integrate and optimize vector stores (e.g., Qdrant, Pinecone, or Milvus) for similarity search, semantic retrieval, and hybrid RAG pipelines.
• Performance & Monitoring: Establish benchmarks, profiling workflows, and monitoring dashboards to maintain low latency and cost-efficient ML inference.
• Cross-functional Collaboration: Partner with frontend, data engineering, and security teams to align on API contracts, CI/CD pipelines, and compliance requirements.
• Mentorship: Coach and review code, design docs, and proofs-of-concept; evangelize Pythonic best practices and architectural patterns across the engineering organization.