Lead AI Engineer

Your Role and Impact

• Architect & Design scalable enterprise-grade GenAI and Agentic AI solutions using SLMs, Crew.AI, and multi-agent orchestration.
• Implement AI governance layer – model monitoring, bias detection, audit trails, explainability, and security controls.
• Lead technical project management – requirement gathering, sprint planning, backlog prioritization, and delivery ownership.
• Hands-on development of LLMOps/MLOps pipelines, CI/CD for AI models, and scalable deployment on Azure / hybrid environments.
• Build and optimize SLM-based systems ensuring performance, scalability, and cost efficiency.
• Stay updated with emerging AI trends, research, and governance frameworks, driving POCs and innovation adoption.
• Ensure compliance with Responsible AI principles, data privacy, and enterprise security standards.
• Mentor and guide teams on GenAI, governance practices, and system design.
  

Key Skills

• Strong expertise in Prompt Engineering, SLMs, Crew.AI, Agentic AI frameworks.
• Proven hands-on experience with Docker, Kubernetes, cloud/on-prem deployments (Azure preferred).
• Knowledge of governance frameworks for AI (bias mitigation, monitoring, compliance).
• Experience in LLMOps/MLOps, CI/CD pipelines, model lifecycle management.
• Strong understanding of system design, scalability, and performance optimization.
• Technical project management and team leadership capabilities.
• Research-driven mindset with ability to evaluate and adopt new AI trends.
  

Your Contribution

Role: Lead – GenAI & Agentic AI Architect / Technical Project Manager (6–8 Years)

Key Responsibilities

• Architecture & System Design
• Architect and implement enterprise-grade GenAI & Agentic AI solutions using SLMs, Crew.AI, Prompt Engineering, and multi-agent orchestration.
• Design scalable and secure cloud/on-prem systems leveraging Azure Stack, Kubernetes, Docker, and distributed AI pipelines.
• Governance & Compliance
• Implement AI governance frameworks including model monitoring, auditability, bias detection, explainability, and security controls.
• Establish guardrails and policy layers for safe deployment of Agentic AI systems in enterprise environments.
• Ensure compliance with data privacy, responsible AI, and regulatory standards.
• Technical Project Management
• Lead cross-functional execution, driving AI/GenAI projects from requirement gathering to delivery with clear technical roadmaps.
• Manage sprints, prioritize backlog, and ensure timely delivery of milestones.
• Hands-on Engineering
• Build and deploy LLMOps/MLOps pipelines for experimentation, versioning, CI/CD of models, and continuous monitoring.
• Lead hands-on development of AI agents, integrating with enterprise APIs and applications.
• Research & Emerging Trends
• Track and evaluate latest advancements in GenAI, Agentic AI, governance frameworks, and SLM optimization.
• Conduct POCs and benchmarking to assess new technologies for enterprise adoption.
• Leadership & Mentorship
• Mentor teams on AI governance, system design, and SLM/Agentic AI engineering.
• Drive knowledge-sharing sessions and contribute to long-term AI strategy.