Job Description

Title : Senior Backend Developer (AI, Python)

Remote

Job Type: Contract

Project description

• We are seeking a hands-on GenAI Engineer to join a team developing production-grade, AI-powered solutions for a major US insurance provider.
• Designed and developed an enterprise-grade Generative AI platform using Python, FastAPI, and FastMCP to automate recruitment workflows and provide intelligent candidate insights. Built scalable, production-ready APIs that integrated with OpenAI GPT and Anthropic Claude models for candidate screening, resume analysis, job matching, and automated recruiter assistance.
• Implemented RAG (Retrieval-Augmented Generation) pipelines using vector databases such as Pinecone/Milvus to provide context-aware responses from enterprise knowledge repositories. Developed AI Agents and custom plugins/skills to automate candidate engagement, interview scheduling, talent recommendations, and workflow orchestration.
• Owned the complete application lifecycle, including architecture design, API development, deployment, monitoring, observability, logging, and performance optimization. Leveraged AI-assisted development tools such as Claude, Codex, and VS Code to accelerate development, debugging, code reviews, and delivery.

Responsibilities

• Design and build backend services that power GenAI applications, integrating Azure OpenAI, OpenAI GPT and Anthropic Claude models.
• Develop and maintain MCP servers using FastMCP to securely expose enterprise data, systems and tools to AI agents.
• Build RAG and agent orchestration services, including retrieval, context assembly and tool execution, using frameworks such as LangChain or LangGraph.
• Use Azure Cosmos DB for both operational data and vector search, with attention to partitioning, RU efficiency and consistency.
• Implement caching with Azure Cache for Redis, including LLM response caching, semantic caching and conversation/session state.
• Build scalable, high-performance REST APIs with Python and FastAPI, handling streaming responses, rate limits, retries and cost controls for LLM providers.
• Containerize services with Docker and deploy and operate them on Azure Kubernetes Service (AKS).
• Build and maintain CI/CD pipelines using GitHub Actions, including automated testing, LLM evaluations and security scanning.
• Implement monitoring and observability for both services and LLM behavior: tracing of LLM and tool calls, token and cost tracking, latency, error rates and quality metrics (Azure Monitor, Application Insights, OpenTelemetry, Langfuse or similar).
• Apply enterprise security practices: secrets management, managed identities, secure MCP tool exposure and protection against prompt injection and data leakage.
• Own services end to end: design, implementation, deployment, production support and incident troubleshooting.
• Use AI-assisted development tools (Claude, Codex) as a core part of the daily engineering workflow.

Skills

Must have

• GenAI experience (primary focus):
• 2+ years of hands-on experience building backend services for GenAI applications, with at least one LLM-based solution delivered to production.
• Practical experience integrating LLM APIs (Azure OpenAI, OpenAI GPT, Anthropic Claude): tool/function calling, structured outputs, streaming, token and context management.
• Hands-on experience with MCP server development (FastMCP preferred).
• Experience implementing RAG pipelines and working with vector search (Cosmos DB vector search, Azure AI Search, pgvector or similar).
• Experience with LLM orchestration frameworks such as LangChain, LangGraph or LlamaIndex.
• Experience with LLM observability and handling of production concerns such as cost, latency, rate limits and provider fallbacks.

Engineering:

• 5+ years of professional backend development experience with a strong focus on Python.
• Solid experience with FastAPI, including async programming, Pydantic and API design.
• Practical experience with Microsoft Azure, including AKS, Azure Cosmos DB and Azure Cache for Redis.
• Experience with Docker, Kubernetes deployments and CI/CD with GitHub Actions.
• Hands-on experience with observability tooling (Azure Monitor, Application Insights, OpenTelemetry, Prometheus, Grafana).
• Good understanding of scalable system design: caching, rate limiting, retries, idempotency and horizontal scaling.
• Daily, confident use of VS Code and AI coding assistants such as Claude and Codex.
• Upper-Intermediate (B2) or higher English, with the ability to communicate directly with US-based stakeholders.

Nice to have

• Experience building GenAI solutions in insurance or financial services.
• Experience with Azure AI Foundry, Azure AI Search or Azure API Management as an AI gateway.
• Experience with multi-agent architectures and LLM evaluation pipelines.
• Infrastructure-as-code (Terraform, Bicep).
• Authentication and authorization with Entra ID, OAuth 2.0 and managed identities.
• Familiarity with compliance requirements for handling PII in regulated industries.

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