Job Description We are looking for a highly motivated and hands-on AI Engineer with robust 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 [email protected] 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 Strong understanding of: 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 Good understanding of: 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.

📌 AI Engineer - INTL India (Bengaluru)
🏢 Insight Global
📍 Bengaluru