Lead AI/ML Engineer

Hinduja Global Solutions (HGS); Hyderabad, Indore District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Hinduja Global Solutions (HGS) seeks an AI Backend Engineer to design, build, and operationalize RAG-based and enterprise AI applications using Python and FastAPI, with production-grade backend services deployed in Azure.

The role requires strong data-domain experience, ownership, and collaboration across cross-functional teams to deliver secure, scalable AI solutions across enterprise data, APIs, identities, and security.

Qualifications

• 8–11 years in software or backend engineering with enterprise data experience.
• Minimum 3+ years hands-on AI, GenAI, LLM, RAG, or AI agents.

Responsibilities

• Proven ability to design and deliver RAG-based and enterprise AI applications integrated with business data, APIs, identity, security, and enterprise systems.

Skills

Python

FastAPI

Azure

RAG

LLM

Data pipelines

API design

Git

Tools

Git

CI/CD

Azure DevOps

Job description

We are seeking a AI Backend Engineer with 811 years of overall professional experience, including 3+ years of hands-on experience in AI and strong exposure to the data domain. This role will be responsible for designing, building, and operationalizing RAG-based applications, enterprise AI applications, AI agents, and scalable backend services using Python and FastAPI. The ideal candidate will bring strong fundamentals of engineering, practical experience with enterprise data integration, retrieval and search pipelines, AI workflow orchestration, and production deployment in the Azure ecosystem. This is a senior-level role that requires technical ownership, sound design judgement, cross-functional collaboration, and the ability to deliver secure, reliable, and business-aligned AI solutions.

Core Requirements (Must Have)

Experience

• 8-11 years of overall professional experience in software engineering, backend engineering, data platforms, or enterprise application development.
• Minimum 3+ years of hands-on experience in AI, including applied experience with GenAI, LLM-based applications, RAG solutions, AI agents, or intelligent automation.
• Strong working experience in the data domain, including enterprise data platforms, data integration, data pipelines, analytics, or data-driven application development.
• Proven ability to design and deliver RAG-based applications and enterprise AI applications that integrate with business data, APIs, identity, security, and enterprise systems.

Backend Engineering

• Strong Python development experience with a focus on clean architecture, reusable components, testing, debugging, performance optimization, and production-grade code quality.
• Proven experience designing, building, and maintaining FastAPI-based backend services, including async execution patterns, REST API design, validation, exception handling, and service reliability.
• Working knowledge of Git, CI/CD practices, environment management, and deployment workflows within the Azure ecosystem.

RAG

• Demonstrated experience designing and implementing RAG systems end to end for enterprise use cases.
• Experience building RAG ingestion pipelines, including document ingestion, parsing, chunking, metadata enrichment, embedding generation, and indexing.
• Hands-on experience with retrieval and search techniques such as vector search, hybrid search, semantic search, re-ranking, retrieval tuning, and quality evaluation.

AI Agents Framework

• Hands-on experience with at least one AI orchestration or agent framework, such as LangChain, Microsoft Agent Framework, Semantic Kernel, or equivalent frameworks.
• Good understanding of agentic architecture patterns, including tool and function calling, state management, memory, planning, orchestration, guardrails, and workflow execution.
• Experience building enterprise AI applications that combine AI agents, RAG workflows, backend APIs, authentication, observability, monitoring, and integration with enterprise data sources.

Data and Storage

• Strong experience with SQL-based data systems, preferably Microsoft SQL Server, including writing, validating, optimizing queries, and supporting data ingestion into relational databases.
• Familiarity with NoSQL data platforms, preferably Azure Cosmos DB, with exposure to managing unstructured or semi-structured data for AI and application workloads.

Ways of Working

• Strong communication, ownership, and collaboration skills, with the ability to work effectively in agile, cross-functional, and globally distributed teams.
• Ability to translate business requirements into scalable technical designs and collaborate with architects, product owners, data engineers, and business stakeholders.

Good to Have (Nice to Have)

• Microsoft Agent Framework experience, including agent hosting patterns, orchestration, and integration with backend services.
• Databricks experience, including Delta tables, notebooks, Unity Catalog, vector search, ML workflows, or AI application integration.