VP / AVP - AI & Digital Transformation

AI Delivery - Cloud-Native Execution - Capability Building - Revenue Growth

Are you an AI leader who can bridge the gap between cutting-edge research and real-world enterprise delivery? We are looking for a hands-on executive to drive AI adoption, own hyperscaler-led solution delivery, and build the next generation of AI capabilities at Innominds.

THE ROLE:

As VP / Senior Director of AI & Digital Transformation at Innominds, you will be the execution engine for our AI-led growth agenda. Unlike a traditional CTO role, this position is delivery-centric you will own AI solution delivery across customer accounts, embed AI into engineering workflows, and support business growth through hands-on solutioning and innovation. You will translate AI strategy into scalable, measurable impact.

EXECUTE:

- Cloud-native AI at production scale

ENABLE:

- AI adoption across every account

GROW:

- Presales wins & practice expansion

KEY RESPONSIBILITIES:

AI Delivery & Cloud-Native Execution:

- Own end-to-end delivery of AI/ML and GenAI solutions on AWS, Azure, and GCP hyperscaler platforms

- Design and implement cloud-native AI architectures leveraging SageMaker, Bedrock, Azure OpenAI, Vertex AI, and related services

- Ensure scalable, secure, and cost-optimised production deployments

- Drive MLOps and LLMOps practices across all AI programs for reliability and repeatability

AI Adoption Across Accounts:

- Identify and implement high-value AI use cases within existing and new customer accounts

- Enable delivery teams to adopt AI-first and cloud-first approaches in day-to-day execution

- Drive adoption of hyperscaler-native AI capabilities and accelerators across active programs

Solutioning & Pre-Sales Support:

- Partner with sales teams to build compelling AI-on-cloud value propositions for prospects and clients

- Lead architecture reviews, technical deep-dives, and RFP / proposal responses

- Participate in client workshops and executive briefings to showcase Innominds' AI capabilities

Capability Building:

- Upskill delivery teams on AI cloud platforms, GenAI frameworks, and MLOps best practices

- Build and maintain a library of reusable AI accelerators and cloud-native frameworks

- Contribute to and help lead the AI Centre of Excellence (CoE)

Governance & Responsible AI:

- Ensure adherence to cloud security standards, AI governance frameworks, and regulatory compliance

- Monitor model performance, cloud costs, and infrastructure optimisation opportunities

- Champion responsible AI practices including bias detection, explainability, and compliance

Collaboration & Ecosystem Alignment:

- Build and nurture strategic relationships with AWS, Azure, and GCP partner teams

- Collaborate closely with Engineering, Data, Product, and Delivery functions

- Align with partner ecosystems for joint go-to-market (GTM) and capability initiatives

WHAT WE'RE LOOKING FOR?

Must-Have:

- Bachelor's / Master's in Computer Science, AI, Data Science, or a related field

- 15-18 years in technology with 3-5 years in an AI/ML leadership role

- Deep understanding of LLMs, ML model architecture, and production-grade AI solution design

- Proven delivery experience on AWS (SageMaker, Bedrock), Azure (OpenAI, ML Studio, Fabric), GCP (Vertex AI, Generative AI Studio).

- Proven Expertise in Claude/ Cursor / Copilot usage for Agentic SDLC Lifecycle.

- Strong hands-on proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn)

- Hands-on experience with MLOps / LLMOps pipelines and tooling

- Strong stakeholder management and executive communication skills

You Will Stand Out If You Have:

- Expertise in Generative AI, prompt engineering, RAG-based architectures, and agentic workflows

- Exposure to AI governance, responsible AI principles, and regulatory compliance frameworks

- Experience building or scaling an AI Centre of Excellence (CoE) or practice

- Certifications in AWS, Azure, or GCP AI & Data platforms

- Track record contributing to pre-sales and winning AI-led engagements

KPI's THAT DEFINE YOUR SUCCESS:

KPI Target Frequency Pillar:

- AI Solution On-Time Delivery - 85% of AI projects on schedule Monthly Delivery

- Production Model Accuracy - 90% accuracy on deployed models Monthly Quality

- AI Use Cases per Account - 3 new AI use cases launched / quarter Quarterly Adoption

- Presales Win Rate - 40% conversion on AI proposals Quarterly Growth

- Cloud AI Cost Variance - 10% over project baseline Monthly Efficiency

- Reusable AI Accelerators Built - 5 production-ready assets / year Semi-Annual Capability

- Team AI Certification Rate - 80% team certified on AI platforms Semi-Annual Capability

- CSAT on AI Engagements - 4.5 / 5 across AI-led accounts Quarterly Customer

This role sits at the epicentre of Innominds' AI growth agenda. Strong execution here opens the path to CTO, Chief AI Officer, or Business Unit Head - the opportunity to shape the future of AI delivery is yours to seize.