AI Engineer

Job Title:AI Engineer – Generative AI & Agentic Systems

Location: Noida | Bangalore | Kolkata

Employment Type: Full-time (5 Days/week from office)

Experience: 3–8 Years

Industry Focus: IT Services, Artificial Intelligence & Analytics

Position Summary

We are looking for a highly skilled AI Engineer – Generative AI & Agentic Systems with 3–8 years of experience in designing, developing, and deploying enterprise-grade AI solutions powered by Large Language Models (LLMs). The ideal candidate will have hands-on expertise in Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), multi-agent architectures, and AI orchestration frameworks. This role involves building intelligent AI assistants, enterprise copilots, autonomous workflows, and scalable AI platforms that drive business innovation and operational efficiency.

Strategic Responsibilities

• Design, develop, and deploy enterprise-grade applications powered by Large Language Models (LLMs) and foundation models.
• Build Retrieval-Augmented Generation (RAG) solutions leveraging vector databases, enterprise knowledge repositories, and GraphRAG architectures.
• Develop conversational AI assistants, enterprise copilots, intelligent chatbots, and workflow automation solutions.
• Implement advanced prompt engineering techniques including Chain of Thought (CoT), ReAct, Self-Reflection, Multi-Step Reasoning, and Tool Calling.
• Design and develop multi-agent AI systems capable of autonomous planning, reasoning, task decomposition, and execution.
• Build agent orchestration frameworks integrating enterprise applications, APIs, and external services.
• Implement agent memory management, communication protocols, and human-in-the-loop workflows.
• Develop scalable AI services, APIs, and reusable AI platform components for enterprise deployments.
• Integrate AI solutions with enterprise platforms including CRM, ERP, Supply Chain, Data Warehouses, and Knowledge Management systems.
• Design and implement AI governance, monitoring, observability, and evaluation frameworks.
• Evaluate AI applications for relevance, groundedness, hallucination, safety, accuracy, and overall performance.
• Build automated evaluation pipelines, testing frameworks, and continuous model validation processes.
• Optimize inference performance, latency, scalability, token utilization, and infrastructure costs.
• Collaborate with Product, Engineering, Data Science, and Business teams to deliver production-ready AI solutions.
• Stay updated with emerging trends in Generative AI, Agentic AI, LLMs, and enterprise AI platforms.

Required Experience:

• 3–8 years of experience in Artificial Intelligence, Machine Learning, or Software Engineering with a strong focus on Generative AI.
• Hands-on experience building applications using Large Language Models (LLMs) and foundation models.
• Strong experience developing Retrieval-Augmented Generation (RAG) systems using vector databases and enterprise knowledge repositories.
• Experience designing and deploying conversational AI applications, enterprise copilots, and intelligent assistants.
• Hands-on experience implementing multi-agent AI systems and autonomous workflows.
• Strong proficiency in Python, FastAPI, REST APIs, and asynchronous programming.
• Experience with AI orchestration frameworks and enterprise AI integrations.
• Strong understanding of prompt engineering, model evaluation, and production deployment best practices.
• Experience developing scalable AI APIs and enterprise-grade AI applications.

Technical Skills:

• Generative AI: OpenAI, Claude, Gemini, Llama, Mistral, Qwen
• Agentic AI Frameworks: LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, Pydantic AI
• RAG & Knowledge Systems: Vector Databases, Knowledge Graphs, GraphRAG
• Programming: Python, FastAPI, REST APIs, Async Programming

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• Cloud & AI Platforms: Azure AI Foundry, Azure OpenAI, Vertex AI, AWS Bedrock, Databricks AI
• DevOps & Deployment: Docker, Kubernetes, GitHub Actions, CI/CD

Good to Have:

• Experience building enterprise-grade AI copilots and digital assistants.
• Experience deploying multi-agent AI systems in production environments.
• Knowledge of AI governance, observability, monitoring, and responsible AI practices.
• Understanding of Model Context Protocol (MCP) and modern AI interoperability standards.
• Experience developing domain-specific AI solutions for Retail, CPG, Banking, Telecom, Healthcare, or Manufacturing.
• Familiarity with MLOps, model lifecycle management, and cloud-native AI deployments.

Educational Qualifications

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.

Soft Skills:

• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Ability to work effectively in cross-functional and agile teams.
• Strong ownership mindset with a focus on delivering scalable AI solutions.
• Passion for innovation and continuous learning in emerging AI technologies.
• Ability to manage multiple priorities in a fast-paced environment.
• Detail-oriented with a strong focus on quality, performance, and business impact.