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Senior Backend Developer (AI, Python)- Remote - Contract

Lorven Technologies, Inc.

Remote • Today

Easy Apply

Contract, Third Party

$60 - $65

Job Details

Skills

GenAI
python
Azure OpenAI
OpenAI GPT
LLM

Summary

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.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10120137
Position Id: 72006-10367-1791386788
Posted 4 hours ago

Fitment

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Job Details

Skills

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Summary

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.

Dice Id: 10120137
Position Id: 72006-10367-1791386788
Posted 4 hours ago

Fitment

Dice Job Match Score™

To see how well you match this job, please log in or create an account.

Once logged in, be sure to complete your profile to get the most accurate match score.

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.

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