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

• 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

• Bachelor's or Master's 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.