Role Overview

We are seeking a highly skilled Agentic AI Senior Lead / Developer to design, develop, and deploy advanced AI systems leveraging autonomous agents, LLMs, and cloud-native architectures. The ideal candidate will have strong expertise in Python, AWS, and Azure, and experience building scalable AI-driven solutions using modern AI frameworks and cloud services.

This role combines hands-on development, architecture design, and technical leadership in delivering intelligent, autonomous, and multi-agent systems for enterprise use cases.

Key Responsibilities

Agentic AI & LLM Development

- Design and implement agent-based AI systems using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar.
- Develop multi-agent orchestration systems with memory, planning, and tool usage capabilities.
- Integrate LLMs (OpenAI, Azure OpenAI, Anthropic, open-source models) into enterprise workflows.
- Implement RAG (Retrieval-Augmented Generation) pipelines using vector databases.
- Build secure, production-grade prompt engineering frameworks.

Python Development

- Develop scalable backend services using Python (FastAPI, Flask, Django).
- Build AI microservices and APIs for enterprise integration.
- Implement async processing, workflow automation, and event-driven systems.
- Ensure high-quality code with unit tests, CI/CD integration, and best practices.

Cloud Architecture (AWS & Azure)

- Design and deploy AI solutions on AWS:

- SageMaker

- Bedrock

- Lambda

- ECS/EKS

- API Gateway

- DynamoDB / RDS
- Implement AI workloads on Azure:





- Azure OpenAI

- Azure ML

- Azure Functions

- Azure Kubernetes Service (AKS)

- Cognitive Services
- Build secure cloud architectures with IAM, VPC, networking, and encryption best practices.
- Implement infrastructure as code (Terraform, CloudFormation, Bicep).

DevOps & MLOps

- Set up CI/CD pipelines for AI applications.
- Manage containerization using Docker & Kubernetes.
- Implement model monitoring, logging, and performance optimization.
- Ensure governance, compliance, and responsible AI practices.

Leadership & Strategy

- Lead AI architecture discussions and solution design workshops.
- Mentor junior developers and AI engineers.
- Define AI adoption strategy and roadmap.
- Collaborate with cross-functional teams (Product, Cloud, Security, Data Engineering).

Required Skills & Qualifications

Technical Skills

- Robust expertise in Python (8+ years preferred).
- Hands-on experience with LLMs and agent frameworks.

- Deep understanding of

- Prompt engineering

- RAG architecture
- Vector databases (Pinecone, FAISS, Weaviate, Azure AI Search)

- API integrations
- Experience with AWS and Azure cloud services.
- Strong knowledge of REST APIs, microservices, and event-driven architecture.
- Experience with Git, CI/CD, Docker, Kubernetes.

Cloud & AI Expertise

- Experience deploying AI systems in production environments.
- Familiarity with AI governance, model evaluation, and monitoring.
- Experience integrating enterprise data sources (SharePoint, SAP, CRM, etc.).

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