Join our team as a Senior Lead / Developer specializing in Agentic AI, where you will architect, build, and deploy sophisticated AI systems. This role focuses on leveraging autonomous agents, large language models (LLMs), and cloud-native technologies. We are looking for extensive experience with Python, AWS, and Azure, alongside a proven track record of creating scalable AI solutions.

This position offers a unique blend of hands-on development, architectural design, and technical leadership, crucial for delivering intelligent, autonomous, and multi-agent systems tailored for enterprise applications.

Spearhead the design and implementation of agent-based AI systems using leading frameworks like LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel. Develop sophisticated multi-agent orchestration systems featuring advanced memory, planning, and tool utilization.

Seamlessly integrate LLMs from providers such as OpenAI, Azure OpenAI, and Anthropic, as well as open-source models, into enterprise workflows. Implement robust Retrieval-Augmented Generation (RAG) pipelines utilizing vector databases and construct secure, production-ready prompt engineering frameworks.

Develop high-performance backend services in Python using frameworks like FastAPI, Flask, or Django. Build and deploy AI microservices and APIs designed for seamless enterprise integration. Implement asynchronous processing, workflow automation, and event-driven architectures, ensuring code quality through unit tests, CI/CD, and adherence to best practices.

Design and deploy AI solutions across AWS, including services like SageMaker, Bedrock, Lambda, ECS/EKS, API Gateway, and DynamoDB/RDS. Implement AI workloads on Azure, leveraging Azure OpenAI, Azure ML, Azure Functions, Azure Kubernetes Service (AKS), and Cognitive Services. Build secure cloud infrastructures employing IAM, VPC, networking, and encryption standards, and manage infrastructure as code using tools like Terraform or CloudFormation.

Establish CI/CD pipelines for AI applications, manage containerization with Docker and Kubernetes, and implement comprehensive model monitoring, logging, and performance optimization. Ensure adherence to governance, compliance, and responsible AI principles.

Provide technical leadership in AI architecture discussions and solution design workshops. Mentor junior developers and AI engineers, contributing to the definition of AI adoption strategies and roadmaps. Foster collaboration with cross-functional teams including Product, Cloud, Security, and Data Engineering.

Possess strong expertise in Python, with at least 8 years of professional experience. Demonstrate hands-on proficiency with LLMs and agent frameworks, coupled with a deep understanding of prompt engineering, RAG architecture, and vector databases (e.g., Pinecone, FAISS, Weaviate, Azure AI Search).

Showcase extensive experience with AWS and Azure cloud services. Exhibit a strong command of REST APIs, microservices, and event-driven architecture. Familiarity with development tools like Git, CI/CD pipelines, Docker, and Kubernetes is essential.

Bring experience deploying AI systems in production environments and a working knowledge of AI governance, model evaluation, and monitoring. Experience integrating with enterprise data sources such as SharePoint, SAP, and CRM systems is highly desirable.