Tech Lead Generative AI

Engineer
Budget :- Open Market Rate

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.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

Tech Lead Generative AI Engineer

Job Description

No Referrers Available