AI Engineer - INTL India

Insight Global; Bengaluru; On-site; INR 3,000,000 - 8,000,000; Full time

Job summary

Insight Global in Bengaluru seeks a hands-on AI Engineer with Generative AI and Agentic AI experience to design, develop, and deploy enterprise AI solutions leveraging LLMs, RAG, embeddings, and vector databases.

The role focuses on building AI applications, orchestrating AI agents, integrating with enterprise systems, and ensuring governance, security, and observability in production deployments. 5-8 years software experience, Python, FastAPI are preferred.

Qualifications

• 5–8 years of overall software engineering experience.
• Minimum 2+ years hands-on experience with Generative AI solutions.
• Experience building and supporting production-grade applications.

Responsibilities

• Design, develop, and deploy enterprise AI applications and services.
• Build and implement Generative AI solutions using LLMs, RAG, embeddings, and vector databases.
• Develop and orchestrate AI agents and multi-agent workflows for business process automation.
• Integrate AI solutions with enterprise applications, APIs, data platforms, and business systems.
• Design AI solutions with guardrails, governance, security, and human-in-the-loop controls.
• Evaluate and improve model performance, prompt effectiveness, and user experience.
• Implement monitoring, observability, testing, and evaluation frameworks for AI applications.
• Collaborate with product owners, architects, and engineering teams to translate requirements into scalable AI solutions.
• Contribute to reusable AI frameworks, accelerators, and platform capabilities.
• Stay current with Generative AI, Agentic AI, and enterprise AI technologies.

Skills

Python

FastAPI

REST APIs

CI/CD

Cloud-native

LLMs

RAG

Embeddings

Agentic AI

Multi-agent

Tools

LangChain

LangGraph

Semantic Kernel

Azure AI Foundry

AutoGen

Job description

Job Description

We are looking for a highly motivated and hands‑on AI Engineer with strong application development experience and expertise in Generative AI and Agentic AI. The ideal candidate should be capable of designing, developing, and deploying enterprise‑grade AI solutions that leverage Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), AI agents, and modern cloud‑native architectures.

The candidate should have a solid understanding of how AI agents work, common design patterns, orchestration approaches, security and governance considerations, and the challenges associated with deploying AI solutions in production environments.

Key Responsibilities

• Design, develop, and deploy enterprise AI applications and services.
• Build and implement Generative AI solutions using LLMs, RAG, embeddings, and vector databases.
• Develop and orchestrate AI agents and multi‑agent workflows for business process automation.
• Integrate AI solutions with enterprise applications, APIs, data platforms, and business systems.
• Design AI solutions with appropriate guardrails, governance, security, and human‑in‑the‑loop controls.
• Evaluate and improve model performance, prompt effectiveness, and user experience.
• Implement monitoring, observability, testing, and evaluation frameworks for AI applications.
• Collaborate with product owners, architects, and engineering teams to translate business requirements into scalable AI solutions.
• Contribute to reusable AI frameworks, accelerators, and platform capabilities.
• Stay current with emerging trends in Generative AI, Agentic AI, and enterprise AI technologies.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [e-mail] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

• 5-8 years of overall software engineering experience.
• Minimum 2+ years of hands‑on experience with Generative AI solutions.
• Experience building and supporting production‑grade applications.

Application Development

• Strong proficiency in Python.
• Hands‑on experience with FastAPI, Flask, or similar backend frameworks.
• Experience developing REST APIs and microservices.
• Familiarity with cloud‑native development and deployment practices.
• Good understanding of Git, CI/CD pipelines, testing, and software engineering best practices.

Generative AI & Agentic AI

• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval‑Augmented Generation (RAG)
• Embeddings and Vector Databases
• AI Evaluation Techniques
• Agentic AI Concepts and Design Patterns
• Multi‑Agent Systems and Agent Orchestration
• Tool Calling and Function Calling

Hands‑on experience with one or more of the following is preferred:

• LangChain
• LangGraph
• Semantic Kernel
• Microsoft AI Foundry / Azure AI Foundry
• AutoGen or equivalent agent frameworks

Cloud & AI Platforms

• Experience working with one or more cloud platforms:
• Microsoft Azure
• AWS
• Google Cloud Platform (GCP)
• Experience with:
• Azure OpenAI or equivalent LLM services
• Azure AI Search or similar search platforms
• Vector Databases and semantic retrieval solutions

Agent Governance & Reliability

• Agent memory and context management
• Hallucination mitigation approaches
• Security and access controls
• Human‑in‑the‑loop workflows
• Prompt injection and AI security risks
• Agent monitoring and observability
• Responsible AI principles
• Cost optimisation and governance Knowledge of Knowledge Graphs and Business Ontologies.
• Understanding of enterprise data platforms and data ecosystems.
• Experience with or understanding of graph databases.
• Experience building AI copilots, enterprise assistants, or conversational AI solutions.
• Exposure to React or other modern front‑end development frameworks.