Experience: 12+ Years Role: Lead AI/ML Engineer / Agentic AI Engineer
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.
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.
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.
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.
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.
Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, Statistics, or a related technical field. Master's or PhD preferred.
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
