Agentic AI Engineer

Agentic AI Engineer - Python, Generative AI & AWS

Job Overview :

We are looking for an experienced Agentic AI Engineer with strong expertise in Python, Generative AI, Large Language Models (LLMs), and AWS AI services to design, develop, and deploy intelligent AI-driven applications and autonomous multi-agent workflows.

The ideal candidate should have hands-on experience building Agentic AI solutions using frameworks such as LangGraph, AutoGen, CrewAI, or Semantic Kernel, along with expertise in Amazon Bedrock, Amazon SageMaker, and AWS cloud infrastructure.

The role involves developing scalable AI architectures, implementing Retrieval-Augmented Generation (RAG) pipelines, integrating enterprise platforms such as Salesforce and ERP systems, and delivering secure, reliable, and production-ready AI solutions.

Key Responsibilities :

- Design, develop, and deploy Agentic AI applications using Python, Generative AI, and Large Language Models (LLMs).

- Build and orchestrate multi-agent workflows using LangGraph, AutoGen, CrewAI, or Semantic Kernel.

- Develop intelligent AI agents capable of autonomous reasoning, planning, tool calling, decision-making, and task execution.

- Design and implement enterprise-grade Generative AI solutions using Amazon Bedrock and Amazon SageMaker.

- Develop and optimize Retrieval-Augmented Generation (RAG) pipelines using embeddings, vector databases, and Amazon OpenSearch Service.

- Implement prompt engineering, context management, model routing, and LLM optimization techniques.

- Design and implement AI guardrails, content filtering, Responsible AI practices, and AI evaluation frameworks.

- Develop and integrate MCP (Model Context Protocol) servers and clients to enable AI agents to interact with external tools, APIs, and enterprise systems.

- Build REST APIs, webhooks, and event-driven integrations to connect AI applications with enterprise platforms.

- Integrate AI agents with Salesforce APIs, CRM systems, ERP platforms, and other enterprise applications.

- Deploy and manage AI workloads using AWS Lambda, Amazon ECS, Amazon EKS, and Amazon S3.

- Develop data ingestion and processing pipelines using AWS Glue and other AWS services.

- Implement secure access management using AWS IAM, AWS KMS, and AWS Secrets Manager.

- Design scalable, fault-tolerant, and production-ready AI architectures on AWS.

- Implement monitoring, logging, observability, and performance optimization for AI applications.

- Establish CI/CD pipelines for automated testing, deployment, and release management.

- Collaborate with architects, product managers, and cross-functional engineering teams to deliver enterprise AI solutions.

Mandatory Skills & Experience :

- Strong hands-on experience with Python programming.

- Expertise in Generative AI, Large Language Models (LLMs), and Agentic AI development.

- Experience building and deploying multi-agent workflows using one or more frameworks : LangGraph, AutoGen, CrewAI, or Semantic Kernel.

- Hands-on experience with AWS AI services, particularly Amazon Bedrock and Amazon SageMaker.

- Strong understanding of Retrieval-Augmented Generation (RAG), embeddings, vector databases, and semantic search.

- Experience with Amazon OpenSearch Service or similar vector search technologies.

- Knowledge of prompt engineering, context management, model routing, and LLM optimization.

- Experience implementing AI guardrails, content filtering, and Responsible AI practices.

- Understanding of MCP servers, MCP clients, and tool integrations.

- Experience developing REST APIs, webhooks, and event-driven integrations.

- Hands-on experience integrating enterprise applications such as Salesforce, CRM, and ERP platforms.

- Experience deploying AI applications using AWS Lambda, ECS, EKS, and S3.

- Knowledge of AWS Glue and data ingestion pipelines.

- Understanding of AWS security services, including IAM, KMS, and Secrets Manager.

- Experience with CI/CD pipelines, application monitoring, logging, and observability.

Skills

Artificial Intelligence, Python, Generative AI, Agentic AI, LangGraph, AWS, RAG, Salesforce