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Sr AI Engineer

Tech Mahindra

2 - 5 years

Bengaluru

Posted: 20/03/2026

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Job Description

AI Application Development

Design and develop AI-powered applications using Generative AI and machine learning models.

Integrate Large Language Models (LLMs) such as OpenAI, Azure OpenAI, or other foundation models into enterprise applications.

Build AI copilots, chatbots, document intelligence solutions, and recommendation systems.

RAG & AI Architecture

Implement Retrieval Augmented Generation (RAG) architectures using vector databases.

Develop pipelines for embedding generation, semantic search, and contextual retrieval.

Optimize prompts, context handling, and response accuracy.

Backend Engineering (.NET)

Build scalable microservices and REST APIs using .NET Core / .NET 8+.

Integrate AI models into backend systems and enterprise platforms.

Implement asynchronous and event-driven processing for AI workloads.

Data & AI Pipelines

Build pipelines for data ingestion, preprocessing, and model inference.

Work with structured and unstructured data including documents, text, and knowledge bases.

AI Deployment & Operations

Deploy AI models and services using containerization and cloud platforms.

Implement monitoring, evaluation, and feedback loops for AI systems.

Ensure security, scalability, and performance of AI services.

Required Skills

Programming & Development

Strong experience in C# / .NET Core / .NET 8

Experience building scalable APIs and microservices

Familiarity with Python for AI development

Generative AI

Experience working with LLMs (OpenAI, Azure OpenAI, Claude, etc.)

Knowledge of Prompt Engineering

Experience implementing RAG architectures

Experience with embeddings and semantic search

AI Frameworks & Tools

Familiarity with LangChain, Semantic Kernel, or similar AI orchestration frameworks

Experience with vector databases (Pinecone, Weaviate, Azure AI Search, etc.)

Knowledge of ML frameworks such as PyTorch, TensorFlow, or Scikit-learn

Cloud & DevOps

Experience with Azure / AWS / GCP

Experience with Docker and CI/CD pipelines

Understanding of MLOps practices

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