Summary
✨ AI‑Generated
A technology organization is looking for a lead developer to design and deploy enterprise generative AI applications. The role covers backend services, frontend interfaces, retrieval systems, AI workflows, and cloud-based integrations.
Highlights
Six-month contract opportunity to lead hands-on AI application development, enterprise integrations, and modern full-stack engineering.
Description
About the Role
We are seeking a Senior Lead Full-Stack GenAI Developer for a 6-month contract engagement to lead the end-to-end hands-on build, integration, and deployment of enterprise GenAI and Agentic AI applications.
Partnering closely with our Principal AI Solution Architect, you will own the full-stack development—spanning backend Python services, frontend interfaces, retrieval pipelines, AI agents, enterprise integrations, and GenAIOps.
Key Responsibilities
Hands-on AI Implementation: Personally author and maintain production-grade Python microservices, custom APIs, retrieval (RAG) systems, and agentic workflows.
Full-Stack Application Building: Create reviewer workbenches, operational dashboards, and user interfaces using React / TypeScript paired with backend-for-frontend APIs.
Enterprise Integration: Seamlessly integrate AI services into enterprise data pipelines, APIs, databases, and platform ecosystems including Microsoft Azure, Databricks, and Microsoft Foundry.
Evaluation & GenAIOps: Design automated evaluation test suites (RAG metrics, model latency, cost, groundedness) and establish CI/CD pipelines, Infrastructure-as-Code (IaC), containerization, and end-to-end telemetry.
Reusable Capabilities & Mentorship: Standardize repeated delivery patterns into reusable SDKs, component libraries, and templates, while mentoring internal engineering team members.
Requirements
Required Qualifications
Seniority & Experience: Proven track record as a Senior or Lead Engineer personally contributing code to production-deployed GenAI systems.
Backend & AI Core: Deep Python proficiency, REST/GraphQL APIs, RAG architectures, vector databases, prompt engineering, agentic frameworks, and automated LLM evaluation practices.
Frontend UI: Strong production skills in React and TypeScript.
Cloud & Platform Ecosystems: Practical experience within Microsoft Azure (Azure OpenAI, Azure AI Search) and Databricks environments.
Data & Ops: Proficiency in SQL, data engineering pipelines, CI/CD, Docker/containers, Infrastructure-as-Code, and runtime telemetry/monitoring.
Important Candidate Note:
Candidates focused primarily on prompt design, research notebooks, architectural oversight, project coordination, or generic web development without recent, hands-on production AI coding, enterprise integration, deployment automation, and production support will not be considered for this role.
