Description
Job Title: Tech Lead – Agentic AI
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)
