What are the responsibilities and job description for the AI Technical Lead position at HNE?
AI Technical Lead – GenAI & Agentic AI
Experience: 10 Years
We are looking for an experienced AI Technical Lead / Senior Engineer to drive the design, development, and deployment of enterprise-scale Generative AI and Agentic AI solutions. The ideal candidate will have deep expertise in LLMs, Agentic AI, AI best practices, and cloud-native AI deployments.
This is a customer-facing role requiring a blend of technical leadership, solution architecture, and forward-deployed engineering capabilities. Experience in Banking & Financial Services domains is preferred.
Key Responsibilities
- Lead the design and delivery of Generative AI and Agentic AI solutions from concept to production.
- Architect and implement Agentic AI systems, including multi-agent workflows, memory architectures, RAG-based solutions and tool integrations.
- Design and develop AI applications leveraging MCP, external APIs and other knowledge bases or business systems.
- Define and implement AI evaluation frameworks covering response quality, groundedness, hallucination detection, agent performance, and observability.
- Leverage AI-assisted development tools such as Claude Code, GitHub Copilot, Cursor or similar platforms to accelerate engineering productivity.
- Deploy, monitor, and optimize AI solutions on Azure, AWS, or Google Cloud platforms.
- Work closely with customers to understand business requirements and translate them into scalable AI solutions.
- Provide technical leadership, mentor engineering teams, and establish AI engineering best practices.
- Collaborate with product, engineering, and business stakeholders to ensure successful solution delivery.
Required Qualifications
- 10 years of experience in AI/ML, Data Science, Software Engineering, or related engineering roles.
- Strong expertise in Python and modern AI development frameworks.
- Strong experience with Generative AI, LLMs, RAG architectures, Agentic AI frameworks, and multi-agent systems.
- Hands-on experience with MCP, agent orchestration frameworks, memory management, and tool-calling architectures.
- Experience with AI evaluation, monitoring, observability, and governance frameworks.
- Hands-on experience with AI coding platforms such as Claude Code, GitHub Copilot, Cursor, or equivalent.
- Experience building and deploying production-grade AI applications and autonomous agent solutions.
- Strong experience with Azure, AWS, or Google Cloud.
- Excellent communication, consulting, and stakeholder management skills.
- Ability to engage directly with customers and operate effectively in a forward-deployed engineering role.
Preferred Qualifications
- Experience with LangGraph, CrewAI, AutoGen or similar agent orchestration frameworks.
- Experience with AI governance, model risk management, and responsible AI practices.
- Familiarity with MLOps, LLMOps, CI/CD pipelines, and cloud-native architectures.
- Experience leading technical teams and delivering enterprise-scale AI transformation initiatives.
- Banking & Financial Services domain experience preferred.