Python Developer

Location: Concord, CA • Work Arrangement: Onsite

About the Role

The ideal candidate is a hands-on Python engineer with strong Agentic AI expertise who can take an AI solution from architecture and development through production deployment. This is an excellent opportunity for a hands-on engineer to work with emerging AI technologies while taking significant technical ownership of solutions moving toward production.

Responsibilities

• Design, develop, and deploy production-ready Agentic AI applications using Python.
• Build intelligent agents and AI-driven workflows to automate marketing campaign activities.
• Develop scalable microservices and REST APIs using Python and FastAPI.
• Design and implement LLM-powered applications using RAG, embeddings, semantic search, and vector databases.
• Develop multi-agent architectures and AI orchestration workflows.
• Integrate LLMs with enterprise applications, APIs, databases, and external services.
• Implement AI guardrails for security, reliability, accuracy, responsible AI, and controlled agent behavior.
• Build robust data and retrieval pipelines supporting RAG applications.
• Design distributed services that can scale reliably in production environments.
• Work with MongoDB for application data, metadata, conversation history, and AI-related workloads.
• Develop automated tests and maintain high standards for code quality and reliability.
• Participate in code reviews and contribute to software engineering standards and best practices.
• Troubleshoot and optimize AI applications and backend services.
• Collaborate with product managers, engineers, data scientists, and business stakeholders.
• Support deployment, monitoring, debugging, and production operations of Agentic AI solutions.
• Evaluate emerging AI models, frameworks, tools, and development approaches.

Requirements

• 5+ years of strong hands-on Python development experience.
• 5+ years of microservices and API development experience.
• 5+ years of MongoDB experience.
• Strong experience developing REST APIs using Python.
• Hands-on experience with FastAPI.
• Strong understanding of distributed systems and microservices architecture.
• Strong experience with LLMs and Retrieval-Augmented Generation (RAG).
• Hands-on experience with vector databases, embeddings, and semantic search.
• Experience implementing AI/Agent guardrails.
• Strong software engineering fundamentals, including:
  • Object-oriented programming
  • Design patterns
  • Unit testing
  • Error handling
  • Logging
  • Code reviews
  • CI/CD
• Strong understanding of production software development and deployment practices.

Preferred Qualifications

• 2+ years of hands-on Agentic AI experience.
• Experience building multi-agent systems.
• Experience with AI orchestration frameworks and agent workflows.
• Experience deploying Agentic AI solutions into production.
• Experience with AWS, Azure, or GCP.
• Experience with AI coding/development tools.
• Experience with prompt engineering and LLM evaluation.
• Experience with LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar frameworks.
• Experience with vector databases such as Pinecone, Weaviate, Milvus, Qdrant, or pgvector.
• Experience with Docker, Kubernetes, and cloud-native deployments.
• Experience with observability and monitoring of AI/LLM applications.
• Experience implementing authentication, authorization, secrets management, and API security.

Technical Environment

• Programming: Python
• APIs: REST, FastAPI
• Architecture: Microservices, Distributed Systems, Multi-Agent Architecture
• AI: LLMs, Agentic AI, RAG, Prompt Engineering, AI Guardrails
• Search & Retrieval: Embeddings, Vector Databases, Semantic Search
• Database: MongoDB
• Cloud: AWS / Azure / GCP
• DevOps: Docker, Kubernetes, CI/CD
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel or equivalent

Interview: 1-hour in-person interview, including coding assessment.