Technical Lead- Azure & AI

About the Role

We are looking for an exceptional Tech Lead — Generative AI Engineer to drive the design, development, and delivery of enterprise-grade AI-powered products and platforms. In this role, you will combine deep expertise in Generative AI, large language models (LLMs), and cloud-native Azure PaaS services with hands-on engineering using .NET and Python. You will lead a team of engineers, set technical direction, and deliver innovative GenAI solutions that create measurable business impact.

This is a senior, hands-on leadership role — you will architect and code alongside your team, mentor engineers, and act as the AI technical authority across product squads.

Key Responsibilities

Technical Leadership

• Lead architecture and end-to-end delivery of production GenAI applications, including RAG pipelines, AI agents, and LLM-powered features.

• Define and enforce engineering standards, best practices, and design patterns across AI and backend systems.

• Drive technical decision-making — model selection, infrastructure choices, build vs buy tradeoffs — with a clear rationale.

• Conduct architecture reviews and provide technical mentorship to a team of 5–8 engineers.

• Collaborate with Product, Data Science, and Platform teams to shape the AI product roadmap.

Generative AI Engineering

• Design and build scalable RAG systems — chunking strategies, vector stores, hybrid search, reranking, and evaluation pipelines.

• Develop and deploy AI agent frameworks using ReAct, tool use, and multi-agent orchestration patterns.

• Implement fine-tuning workflows (LoRA, QLoRA) and prompt engineering strategies for production use cases.

• Build robust evaluation frameworks: LLM-as-judge, hallucination detection, RAGAS, and A/B testing for AI outputs.

• Apply guardrails, safety checks, and responsible AI practices across all GenAI products.

Azure PaaS & Cloud Engineering

• Architect and operate GenAI solutions on Azure — Azure OpenAI Service, Azure AI Search, Azure Machine Learning, and Azure Kubernetes Service (AKS).

• Design event-driven and microservices architectures using Azure Service Bus, Event Grid, Azure Functions, and API Management.

• Manage infrastructure as code using Bicep or Terraform; implement CI/CD pipelines via Azure DevOps.

• Ensure security, compliance, and cost efficiency across Azure-hosted AI workloads.

.NET & Python Development

• Build high-performance backend services and APIs using .NET 8 / ASP.NET Core for enterprise integrations.

• Develop AI/ML pipelines, data processing, and orchestration logic in Python (FastAPI, LangChain, LangGraph, Semantic Kernel).

• Design and maintain polyglot persistence layers — Azure SQL, Cosmos DB, Azure Cache for Redis, and vector databases (Azure AI Search, pgvector).

• Enforce clean code principles: SOLID, DDD, TDD, and code review discipline.

Required Skills & Experience

Must-have

• 8+ years of software engineering experience, with 2+ years in a tech lead or principal engineer role.

• Hands-on experience designing and shipping production Generative AI applications (RAG, LLM APIs, agents).

• Strong proficiency in Python for AI/ML engineering (LangChain, LangGraph, Semantic Kernel, or similar frameworks).

• Strong proficiency in .NET / C# for enterprise backend and API development.

• Deep expertise in Azure PaaS: Azure OpenAI, Azure AI Search, Azure ML, AKS, Azure Functions, Service Bus.

• Experience with vector databases and semantic search (Azure AI Search, pgvector, Pinecone, Weaviate, or Chroma).

• Proven ability to lead and grow engineering teams; track record of technical mentorship.

• Strong system design skills — able to design for scale, reliability, and cost-efficiency in cloud-native environments.

• Experience with fine-tuning LLMs using LoRA / QLoRA and managing training pipelines on Azure ML.

• Experience with multi-agent frameworks — LangGraph, AutoGen, CrewAI, or similar.

• Knowledge of model quantization and LLM inference optimization (vLLM, ONNX Runtime, TGI).

• Experience with DSPy, prompt evaluation frameworks, or automated prompt optimization.

• Azure certifications (AI-102, AZ-204, AZ-305) or equivalent cloud credentials.

• Experience with multimodal AI models (GPT-4o, vision, audio) or document intelligence pipelines.

Tech Stack

AI / LLMs Azure OpenAI (GPT-4o, Ada), LangChain, LangGraph, Semantic Kernel, RAGAS, LlamaIndex

Cloud — Azure Azure AI Search, Azure ML, AKS, Functions, Service Bus, Event Grid, APIM, Bicep, DevOps

Languages .NET 8 / C#, Python 3.11+

Frameworks ASP.NET Core, FastAPI, Entity Framework Core

Data & Storage Azure SQL, Cosmos DB, Redis Cache, Azure Data Lake, pgvector

DevOps & Tooling Azure DevOps, GitHub Actions, Docker, Kubernetes, Terraform

Observability Azure Monitor, Application Insights, OpenTelemetry, LangSmith

What We Offer

• Opportunity to build AI-first products from the ground up with a high degree of technical ownership.

• Competitive compensation including performance bonus and equity / ESOP.

• Dedicated learning budget for AI research, conferences, and certifications.

• Access to cutting-edge Azure AI services, GPU compute, and enterprise LLM APIs.

• Flexible hybrid work model with a collaborative, engineering-driven culture.

• Direct influence on AI strategy and architecture decisions at the organisation level.