AI/ML Engineering Leader

We are seeking a vision-driven AI/ML Engineering Leader to architect and scale intelligent enterprise solutions that transform business outcomes through innovation and automation. The ideal candidate will bring deep techno-functional expertise in LLMs, Generative AI frameworks, Agentic AI workflows, and MLOps, driving enterprise-scale AI adoption and measurable impact.

Key Responsibilities:

AI/ML Strategy & Transformation:

- Define and execute AI/ML roadmaps aligned with business KPIs.

- Lead enterprise-scale transformations by architecting end-to-end machine learning ecosystems.

Generative AI & LLM Solutions:

- Design and implement Retrieval-Augmented Generation (RAG) solutions and agentic AI workflows.

- Fine-tune LLMs for domain-specific applications and optimize inference efficiency using quantization and PEFT techniques.

MLOps & Model Lifecycle Management:

- Build scalable CI/CD pipelines for model deployment and monitoring.

- Develop explainability dashboards and ensure compliance with ethical AI governance.

NLP & Text Analytics:

- Deliver advanced NLP solutions leveraging transformer-based architectures for knowledge management and automation.

AI Integration with ITSM Platforms:

- Implement AI-driven service transformation for platforms like ServiceNow, enabling intelligent incident management and anomaly detection.

Cloud-Native AI Development:

- Architect and deploy AI solutions on AWS SageMaker and Bedrock environments.

Data Engineering & Governance:

- Design scalable ETL pipelines and enforce data governance standards for AI readiness.

Leadership & Mentorship:

- Foster high-performing global teams and promote AI adoption through ethical practices and cross-functional collaboration.

Required Skills & Qualifications:

- Technical Expertise: Python, R, TensorFlow, PyTorch, LangGraph, AWS Bedrock, SageMaker.

- AI/ML Specialization: LLM fine-tuning, RAG, Generative AI, NLP, Vision AI.

- MLOps Proficiency: CI/CD pipelines, model monitoring, explainability, compliance frameworks.

- Cloud Experience: AWS cloud-native AI development.

- Soft Skills: Strategic thinking, leadership, mentoring, and stakeholder management.

- Experience: 10+ years in IT/consulting with at least 5+ years in AI/ML engineering leadership roles.

Preferred Qualifications:

- Experience in agentic AI workflow design and autonomous systems.

- Proven track record of delivering enterprise-scale AI transformations.

- Familiarity with ethical AI governance and regulatory compliance frameworks.