AI Development Lead

Job Summary
We are looking for a Lead AI Full-Stack Engineer to define the technical vision architecture and execution strategy for our next-generation AI-native this high-impact role you will lead a cross-functional team of developers while remaining hands-on in code.
You will own end-to-end technical direction across our Java and Python Microservices enterprise React applications cloud systems (Azure) and advanced LLM/RAG orchestration pipelines.
Key Responsibilities

• Technical Leadership & Strategy: Establish end-to-end AI application architecture establish best practices for prompt engineering latency optimization cost control and set engineering standards across frontend backend and AI stacks.
• Team Mentorship & Delivery: Guide and mentor cross-functional engineers (510 team members) conduct code reviews unblock technical issues and partner with Product and Design leaders to map product roadmaps into technical deliverables.
• AI & RAG System Architecture: Architect resilient Retrieval-Augmented Generation (RAG) pipelines multi-agent frameworks and real-time semantic search using tools like LangChain LlamaIndex or AutoGen.
• Full-Stack & Microservices Design: Oversee robust scalable Microservices engineered in Java (Spring Boot) and Python (FastAPI/Django) integrated with component-driven React/TypeScript frontends.
• Enterprise Azure Infrastructure: Own cloud architecture strategy on Microsoft Azure (Azure OpenAI Azure AI Search AKS Container Apps) prioritizing high availability strict security protocols and cost governance.
• AI Governance & Reliability: Implement guardrails for LLM safety PII detection fallback mechanisms hallucination evaluation metrics and continuous performance monitoring.

• Experience: 7 years in full-stack engineering including 2 years leading engineering initiatives or technical teams and building AI-native applications in production.
• Frontend: TypeScript state management architectures micro-frontends and web performance optimization.
• Backend: Mastery of Java (Spring Boot) and Python (FastAPI Flask); expertise in Microservices design asynchronous patterns and API gateways.
• AI / LLM Orchestration: Deep expertise with RAG architectures Vector DBs (Pinecone Qdrant Azure AI Search pgvector) agentic workflows model routing and token optimization.
• Cloud & DevOps: Advanced skills in Azure cloud infrastructure Docker Kubernetes (AKS) Infrastructure-as-Code (Terraform/Bicep) and CI/CD automation.
• Leadership: Track record of mentoring developers driving architectural decisions and communicating complex AI tradeoffs to executive leadership.
• Proven experience fine-tuning open-source models (Llama Mistral) or building enterprise-wide semantic caches.
• Experience with multi-agent design patterns (AutoGen CrewAI) and complex function-calling structures.
• Deep knowledge of enterprise AI compliance data privacy and Responsible AI frameworks.