Description

Key Skills: Agentic AI, AI/ML, Generative AI

Roles and Responsibilities:

• Design and develop AI agents and agentic AI applications using LLMs.
• Build autonomous and semi-autonomous agents capable of reasoning, planning, and tool execution.
• Develop multi-agent workflows for complex business use cases.
• Implement RAG (Retrieval-Augmented Generation) pipelines.
• Integrate LLMs with external APIs, databases, enterprise systems, and tools.
• Develop agent workflows using LangGraph, LangChain, or LlamaIndex.
• Implement prompt engineering, function/tool calling, memory, and context management.
• Work with vector databases for semantic search and knowledge retrieval.
• Evaluate and optimize agent performance, accuracy, latency, and cost.
• Deploy scalable AI solutions using cloud platforms such as AWS, Azure, or GCP.
• Develop APIs and microservices to integrate AI agents with enterprise applications.
• Implement monitoring, security, guardrails, and responsible AI practices.
• Collaborate with Data Scientists, ML Engineers, Software Engineers, and business stakeholders.

Skills Required:

Mandatory Skills

• Python
• Generative AI / GenAI
• LLMs
• Agentic AI / AI Agents
• LangChain / LangGraph
• RAG
• Prompt Engineering
• Tool Calling / Function Calling
• REST APIs
• Vector Databases
• AI/ML application development

Good to Have

• AWS Bedrock / SageMaker
• Azure OpenAI
• Google Vertex AI
• OpenAI APIs
• LlamaIndex
• Pinecone / FAISS / OpenSearch
• Multi-Agent frameworks
• Docker / Kubernetes
• FastAPI
• CI/CD
• MLOps
• AI evaluation and observability tools
• Strong programming and problem-solving skills.
• Experience building and

Education: Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or a related field

Key Skills

Education

Any Graduate