Job Title: Lead AI/ML Engineer Generative AI / Agentic AI



THIS IS AND W2 POSITION, Candidates who does not match the requirements please do not submit the profile



Work Auth: and OPT/STEM OPT

Experience: 12+ Years Role: Lead AI/ML Engineer / Agentic AI Engineer

Job Summary

We are seeking an experienced Lead AI/ML Engineer with 12+ years of overall IT experience and strong hands-on expertise in Generative AI, Agentic AI, Python, LLMs, and multi-agent orchestration frameworks.

The ideal candidate will be responsible for designing, developing, and deploying enterprise-grade AI agents, implementing intelligent workflow automation, and building scalable AI-powered applications.

This role requires strong technical leadership, enterprise AI architecture experience, and the ability to establish reusable AI frameworks, security standards, and development best practices.

Primary Skills Must Have

• Python: Strong programming, scripting, and automation experience.

• Generative AI: Experience developing enterprise AI-powered applications.

• Agentic AI: Hands-on experience designing and deploying autonomous AI agents.

• LangGraph, LangChain, and CrewAI: Experience with agent development and orchestration frameworks.

• LLMs: Experience integrating and optimizing Large Language Models.

• Multi-Agent Systems: Agent collaboration, planning, delegation, and workflow orchestration.

• Prompt Engineering: Experience developing and optimizing prompts for LLM-powered applications.

• Workflow Automation: Experience building intelligent workflows using Python and AI frameworks.

Required Technical Skills

• 12+ years of overall IT, software engineering, or AI/ML experience.

• Strong Python programming experience, including NumPy, pandas, and SciPy.

• Hands-on experience building production-ready Generative AI and Agentic AI applications.

• Experience with LangGraph, LangChain, and CrewAI.

• Strong understanding of multi-agent architecture and orchestration patterns.

• Experience developing reusable agent frameworks and reference architectures.

• Knowledge of LLM integration, prompt optimization, and agent design patterns.

• Experience integrating AI agents with enterprise applications using REST APIs.

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.

• Knowledge of event-driven and batch processing architectures.

• Experience implementing AI security, RBAC, authorization models, and governance.

• Knowledge of AI agent evaluation, hallucination detection, and output validation.

• Experience implementing human-in-the-loop workflows.

• Experience with AI application deployment, monitoring, and scalability.

• Understanding of LLM performance optimization, latency, token consumption, and operational costs.

• Strong technical leadership, mentoring, and problem-solving skills.

Preferred Skills

• Model Context Protocol (MCP).

• Retrieval-Augmented Generation (RAG).

• Vector databases and semantic search.

• Enterprise integrations with Microsoft Teams, SharePoint, email, and other applications.

• Automated testing and monitoring of AI applications.

• Advanced machine learning and statistical modeling.

• Experience with CI/CD and MLOps.

• Experience in automotive, aerospace, heavy equipment, construction, mining, or industrial domains.

Key Responsibilities

• Lead the architecture, design, and development of enterprise AI/ML solutions.

• Design and deploy AI agents using modern Agentic AI frameworks.

• Develop multi-agent workflows using LangGraph, LangChain, and CrewAI.

• Build automated workflows using Python.

• Develop reusable AI agent frameworks and reference architectures.

• Integrate LLMs with enterprise applications, APIs, and data sources.

• Implement prompt engineering and agent optimization techniques.

• Design and implement human-in-the-loop workflows and approval mechanisms.

• Establish AI security, access controls, and governance standards.

• Develop AI evaluation and testing frameworks to monitor accuracy, reliability, and hallucinations.

• Optimize AI applications for performance, scalability, latency, and cost.

• Support cloud deployment, monitoring, and operationalization of AI solutions.

• Collaborate with business stakeholders and technical teams to translate requirements into scalable AI solutions.

• Provide technical leadership and mentor AI/ML engineers.

• Establish engineering standards and reusable best practices across AI initiatives.

• Stay current with emerging Generative AI technologies and continuously improve existing solutions.

Education

Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, Statistics, or a related technical field. Master's or PhD preferred.

Required Experience

12+ years of overall IT experience, including strong hands-on experience in Python, AI/ML engineering, Generative AI, Agentic AI, and enterprise application development.

Candidates should have demonstrated experience delivering production-ready AI solutions and providing technical leadership to engineering teams