Technical Lead - Agentic AI Solutions

Process Manager

Description

Role Overview: 

The Tech Lead – Agentic AI will spearhead the design, development, and deployment of agentic AI solutions that transform enterprise operations and decision-making. This role requires deep technical expertise in AI system architecture, LLM orchestration, and automation frameworks, combined with leadership capabilities to guide multi-disciplinary teams and deliver high-impact AI programs. 

Key Responsibilities: 

1. Technical Leadership & Architecture • Own the end-to-end technical strategy and architecture for the Agentic AI program, ensuring scalability, security, and enterprise alignment. • Lead design and development of intelligent agent workflows leveraging LLMs, reasoning engines, and autonomous orchestration frameworks (e.g., LangChain, AutoGen, Copilot Studio). • Establish coding standards, MLOps practices, and integration frameworks to ensure quality and maintainability. • Collaborate with solution architects, data engineers, and DevOps to design cloud-native, production-ready AI systems. 2. Solution Design & Delivery • Translate business and functional requirements into detailed technical specifications, solution blueprints, and implementation plans. • Oversee AI model integration, API development, and data pipeline orchestration. • Drive experimentation, fine-tuning, and continuous improvement of agentic workflows for accuracy, responsiveness, and efficiency. • Ensure delivery timelines, quality standards, and compliance benchmarks are met across all AI initiatives. 3. Team & Program Leadership • Mentor and guide engineers, data scientists, and automation developers in building AI-powered solutions. • Lead agile sprints, design reviews, and release planning sessions for multiple concurrent workstreams. • Partner closely with business analysts, product owners, and stakeholders to ensure alignment between technical delivery and business value. • Manage vendor or partner engagements for AI platform integration and model deployments. 4. Innovation, Optimization & Governance • Evaluate emerging tools, LLM frameworks, and agent orchestration technologies to continuously enhance solution capabilities. • Define and monitor performance metrics (e.g., automation rate, accuracy, response latency, ROI). • Implement governance practices for AI model explainability, data privacy, and ethical compliance. • Champion reusability, modularity, and best practices for sustainable AI engineering. 

Qualifications & Skills: Minimum Qualifications: 

• Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related technical discipline. • 8–12 years of experience in technology roles with at least 3 years in AI/automation leadership. • Proven experience in designing and deploying agentic AI or LLM-based systems in enterprise settings. • Expertise in Python, APIs, vector databases, and orchestration frameworks (LangChain, AutoGen, Copilot Studio, or similar). • Strong understanding of cloud-native AI development (Azure OpenAI, AWS Bedrock, Google Vertex AI). • Solid grasp of MLOps, prompt engineering, and retrieval-augmented generation (RAG) patterns. Experience integrating AI agents with business systems (CRM, ERP, ITSM, or custom workflows