Generative AI Engineer - LangChain & Cloud Infra

Brooksource

Birmingham (AL)

Hybrid

USD 62,000 - 83,000

Full time

5 days ago

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Benefits offered by this job

Comprehensive benefits

Hybrid work

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Job summary

Brooksource is seeking an AI Developer in Birmingham, AL for a hybrid, contract-to-hire role. You will design, build, and deploy AI-powered applications using Python, LangChain, and modern AI platforms, collaborating with architects and engineers to deliver scalable, enterprise-grade solutions.

The role emphasizes creating agent-based workflows, integrating LLMs, and deploying containerized AI apps in Kubernetes/OpenShift.

Qualifications

3+ years of software engineering experience with strong Python development.
Hands-on AI development with LangChain, LangGraph, or similar agent frameworks.
Experience with LLMs, Generative AI, and MCP tools.
Experience with AWS Bedrock / Azure AI Foundry / Azure OpenAI.
Experience deploying containerized apps using Kubernetes or OpenShift.
Experience working in Agile software development teams.

Responsibilities

Design, develop, and deploy AI-powered applications using Python and modern AI development frameworks.
Build Generative AI solutions leveraging LangChain, LangGraph, and enterprise AI platforms.
Develop agent-based applications and workflows utilizing MCP tools and integrations.
Integrate Large Language Models (LLMs) into enterprise applications via cloud platforms like AWS Bedrock or Azure AI Foundry.
Develop Retrieval-Augmented Generation (RAG) workflows and integrate vector databases as needed.
Create and deploy containerized AI applications within Kubernetes and OpenShift environments.
Collaborate with architects, product teams, engineers, and business stakeholders to translate requirements into scalable AI solutions.
Implement testing, monitoring, and observability practices to ensure reliable AI application performance.
Optimize AI applications for scalability, security, and operational efficiency.
Contribute to AI development standards, reusable frameworks, and engineering best practices.
Evaluate emerging AI tools and technologies to improve solution delivery.
Support production deployments and ongoing enhancements of AI-driven applications.