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.