Architect

'Role Overview.

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.