The AI Agentic Native Engineer will be responsible for designing and developing autonomous AI agents and agentic workflows to automate complex operational and decision-making processes. The role focuses on building systems that utilize multi-step reasoning, task orchestration, and collaboration between multiple agents using advanced frameworks.
Key Responsibilities
Agentic Workflow Development: Design and develop AI agents using LangChain and LangGraph to enable multi-step reasoning and task orchestration.
LLM Implementation: Build production-grade applications using Large Language Models (LLMs), implementing Retrieval-Augmented Generation (RAG), prompt engineering, and context management.
Model Optimization: Fine-tune models using PEFT/LoRA techniques to improve domain adaptation and optimize inference performance.
Pipeline & API Integration:
Build scalable end-to-end ML pipelines and expose inference services via REST APIs using FastAPI.
Cloud Orchestration: Deploy and manage serverless architectures and event-driven workflows using AWS Lambda, Step Functions, and API Gateway.
Technical Qualifications
AI Frameworks: Deep expertise in LangChain, LangGraph, and vector databases like Pinecone or FAISS.
Machine Learning: Proficiency in Python, PyTorch, TensorFlow, and Transformers.
Cloud Infrastructure: Hands-on experience with AWS (SageMaker, S3, Lambda) or Azure AI.
DevOps/MLOps: Experience with containerization (Docker, Kubernetes) and CI/CD pipelines for AI systems."
📌 Architect Chennai
🏢 Virtusa
📍 Chennai
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