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.