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Senior Backend Developer (AI, Python)

Luxoft·Salary not specified

Primary stack

DockerKubernetesPythonCI/CDFastAPIAzure

Nice to have's

Azure AI FoundryAzure API Managementmulti-agent architecturesTerraformBicepEntra IDOAuth 2.0managed identitiescompliance requirements

Job description

About the Position

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.

Requirements

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.

We Offer

  • Competitive salary
  • Opportunity to work remotely from the United States
  • Professional growth and development opportunities
  • Collaborative and innovative work environment

About the Company

DXC Luxoft is a leading provider of technology and consulting services, specializing in delivering innovative solutions to clients across various industries. Our team is dedicated to pushing the boundaries of technology to create impactful and scalable solutions.

Application

To apply for this position, please submit your resume and cover letter detailing your relevant experience and skills. We look forward to reviewing your application!

© Luxoft. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.

A provider of software development services and innovative IT solutions with a worldwide customer base consisting mainly of large multinational corporations.

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