Lead AI Engineer
5 days ago
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.
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