AI Engineer (AI / ML)

Responsibilities:
Design and develop AI-powered applications, intelligent assistants, and enterprise automation solutions.
Build and deploy multi-agent systems, tool-using agents, and conversational AI/chatbot platforms.
Develop and optimise Retrieval-Augmented Generation (RAG) architectures for enterprise use cases.
Integrate LLMs with internal and external tools using Model Context Protocol (MCP) and other agent frameworks.
Implement secure, scalable, and production-ready AI solutions aligned with enterprise standards.
Work with cloud-native AI services, with a strong preference for AWS Bedrock and related AI infrastructure.
Collaborate with product, engineering, and security teams to define AI architecture and implementation strategies.
Evaluate and integrate leading LLM providers and SDKs, including Anthropic Claude and related Agent SDKs.
Drive best practices around AI governance, observability, security, and responsible AI adoption.
Mentor engineers and contribute to technical leadership across AI initiatives.
Requirements:
B. Tech/M. Tech in Computer Science, Engineering, or a related field.
Candidates from IITs, NITs, and other premier engineering institutes will be strongly preferred.
8+ years of overall software engineering experience.
Proven experience building and deploying AI/ML applications in production environments.
Hands-on experience working with LLMs, GenAI, and agent-based architectures.
Technical Skills:
Strong proficiency in at least one of: Python, TypeScript. NET / C#.
Experience building: Multi-agent systems, AI agents and autonomous workflows, Enterprise chatbots and conversational AI platforms, AI-powered automation solutions.
Strong experience with: Retrieval-Augmented Generation (RAG), Vector databases and semantic search, Prompt engineering and LLM orchestration, Model Context Protocol (MCP) integrations, Tool-calling frameworks and agent architectures.
Experience working with: AWS Bedrock (strongly preferred), Anthropic Claude and Agent SDKs, OpenAI, Anthropic, or similar LLM providers, Cloud-native AI services and infrastructure.
Understanding of: AI security frameworks, LLM security and governance, Secure AI application development, and Enterprise-scale AI deployment patterns.

Experience
8-12 yrs