AI/ML Engineer

Introduction

We are looking for an experienced AI/ML Engineer / Agentic AI Developer to join a team building next-generation AI-powered solutions. The ideal candidate will have hands-on experience developing AI/ML or Agentic AI solutions, combined with strong software development skills in Python and/or Java and extensive experience with AWS cloud services. The role will focus on designing and developing intelligent, AI-driven applications using modern agentic frameworks, GenAI tools, and enterprise cloud technologies.

Responsibilities

• Design, develop, and deploy Agentic AI/ML solutions for enterprise applications.
• Build AI agents and multi-agent workflows using LangGraph and related frameworks.
• Develop and integrate Model Context Protocol (MCP)-based tools and services.
• Leverage Generative AI tools, LLMs, and APIs to build intelligent applications.
• Apply prompt engineering techniques to improve model performance, reliability, and response quality.
• Develop scalable backend services and APIs using Python and Java.
• Integrate AI/ML capabilities with existing enterprise applications and cloud platforms.
• Design and implement solutions leveraging AWS services and cloud-native architectures.
• Develop automated CI/CD pipelines for building, testing, and deploying AI/ML applications.
• Collaborate with architects, developers, data scientists, and product teams to deliver production-ready AI solutions.
• Implement appropriate monitoring, testing, security, and operational practices for AI-enabled applications.

Requirements

Required Skills

• Hands-on experience building Agentic AI / AI/ML solutions in a production or enterprise environment.
• Strong development experience with Python and/or Java.
• Strong hands-on experience with AWS cloud services and cloud-native application development.
• Experience with LangGraph for building agentic workflows.
• Experience with MCP (Model Context Protocol) and AI tool integrations.
• Strong understanding of Generative AI / LLM technologies.
• Experience with Prompt Engineering and LLM application development.
• Strong understanding of software development, APIs, microservices, and application architecture.
• Experience building and maintaining CI/CD pipelines.
• Ability to work in an enterprise development environment and collaborate across technical teams.

Preferred Qualifications

• Experience with multi-agent architectures and AI orchestration.
• Experience integrating LLMs with enterprise data sources, APIs, and external tools.
• Knowledge of AWS AI/ML services such as Amazon Bedrock, SageMaker, Lambda, ECS/EKS, API Gateway, and related services.
• Experience with containers and Kubernetes.
• Familiarity with observability, automated testing, and DevSecOps practices.
• Experience taking GenAI/Agentic AI prototypes into production-scale applications.

Core Technical Skills

AI / GenAI: Agentic AI, AI/ML, LLMs, Generative AI, Prompt Engineering
Agent Frameworks: LangGraph, MCP, GenAI Tools
Programming: Python, Java
Cloud: AWS
DevOps: CI/CD
Architecture: APIs, Microservices, Cloud-Native Applications

Ideal Candidate Profile

The ideal candidate is a hands-on software engineer with strong AI/ML and GenAI experience, rather than someone focused solely on research or data science. They should have demonstrated experience building and deploying agentic AI solutions, strong Python/Java development capabilities, and significant AWS experience.