AI Corporate Trainer

Key Responsibilities

1.AI Consulting & Enterprise Engagements

Lead and support enterprise AI consulting engagements from discovery and use-case identification through PoC design, production deployment, and adoption.

Engage with CXO, business, and technology stakeholders to define AI strategy, use-case portfolios, GenAI adoption roadmaps, and ROI frameworks.

Conduct AI maturity diagnostics, architecture reviews, and readiness assessments across client organizations.

Create reusable consulting assets: industry playbooks, reference architectures, evaluation rubrics, governance templates, and implementation toolkits.

2.PoC Development & Accelerator Building

Design, prototype, and deliver enterprise-grade AI PoCs with clearly defined success metrics, evaluation criteria, and production-readiness checklists.

Build and maintain a library of repeatable GenAI accelerators RAG starter kits, agent templates, workflow copilots, and domain-specific demo packs.

Apply best practices for hallucination mitigation, prompt engineering, guardrails, security review, and responsible AI governance.

Contribute to the SAI PoC engine defining standards for use-case selection, cost/latency/accuracy targets, and PoC-to-production transition playbooks.

3.AI Training Design & Delivery

Design and deliver high-impact AI learning programs from CXO executive immersions and functional tracks to technical practitioner bootcamps and role-based journeys.

Develop hands-on lab guides, capstone projects, case studies, and real-world simulations that drive measurable learner outcomes.

Translate complex AI/ML concepts into clear, compelling narratives for diverse audiences from the boardroom to the engineering floor.

Contribute to certification standards, competency frameworks, assessment rubrics, and quality assurance processes for SAI training products.

4.AI Platform & Labs Contribution

Contribute to the SAI AI Enablement Platform building sandbox environments, lab exercises, auto-evaluation harnesses, and prompt/agent pattern libraries.

Align platform components with consulting accelerators and training modules to create a seamless practitioner experience.

Participate in model evaluation, LLMOps tooling, and responsible AI toolchain design.

5.Thought Leadership & Community

Publish POVs, white papers, blogs, and research on applied AI establishing SAI India's intellectual authority in the market.

Represent SAI at industry conferences, webinars, university events, and partner forums.

Mentor junior AI practitioners, researchers, and interns within the SAI ecosystem.

What You Must Bring

A.Deep AI Expertise (Non-Negotiable)

815+ years of experience in AI/ML, with at least 46 years focused on GenAI, LLMs, and applied enterprise AI.

Hands-on proficiency in: LLMs (GPT-4, Claude, Gemini, Llama, Mistral), RAG architectures, prompt engineering, AI agents, and multi-modal AI.

Working knowledge of: LLMOps/MLOps, evaluation frameworks, guardrails, vector databases, orchestration frameworks (LangChain, LlamaIndex, AutoGen, CrewAI).

Experience with cloud AI platforms: Azure OpenAI, AWS Bedrock, Google Vertex AI, Hugging Face.

B.Proven Build Record: PoCs + Production

Personally led at least 35 enterprise AI PoCs with measurable outcomes not just advisory, but hands-on design and delivery.

Demonstrated experience taking AI solutions from prototype to production in real enterprise environments.

Experience with at least one of the following at scale:

RAG pipeline design and optimization

AI agent architecture and deployment

Enterprise GenAI platform components (guardrails, evaluation, model routing)

AI skilling/training platform (labs, sandboxes, auto-eval, certification)

C.Consulting & Communication Strength

Demonstrated track record of delivering AI transformation engagements including stakeholder management, value articulation, and executive communication.

Ability to run structured workshops, design sprints, and discovery sessions with business and technology leaders.

Strong written communication capable of producing compelling proposals, POVs, case studies, and client deliverables independently.

D.Training & Facilitation Excellence

Experience designing and delivering both executive (CXO/management) and technical (developer/data scientist) AI programs.

Ability to build structured learning journeys: outcomes curriculum labs assessments certification.

High-energy facilitation skills; comfortable leading intensive bootcamps, workshops, and executive roundtables.

E.Responsible AI & Enterprise Readiness

Working knowledge of AI ethics, bias mitigation, explainability, data privacy (GDPR, DPDP Act), and enterprise AI governance.

Understanding of AI risk frameworks and responsible deployment practices.