Lead

Company: Innomax IT Solutions Pvt. Ltd.

Location: Hyderabad

Employment Type: Full-time

Function: AI, GenAI, GCC Transformation, Enterprise Automation

Seniority: Senior Lead / Architect / Practice Head

Innomax IT Solutions Pvt. Ltd. is building AI-first technology and transformation capabilities for Global Capability Centres. As GCCs move from cost-arbitrage centres to innovation-led value centres, Innomax IT aims to support them with AI platforms, automation, copilots, agentic workflows, knowledge systems, and productivity solutions.

We are looking for an AI / GenAI Leader for GCC Transformation who can design and lead AI solutions specifically for GCC operations, global delivery, shared services, enterprise productivity, and innovation ownership.

The AI / GenAI Leader will own the strategy, architecture, and execution of AI-led solutions for GCCs. The role requires someone who understands how GCCs function across technology, finance, HR, procurement, operations, customer support, analytics, cybersecurity, product engineering, and shared services.

The candidate should be able to convert GCC pain points into scalable AI solutions such as enterprise copilots, GenAI agents, RAG platforms, workflow automation systems, productivity intelligence tools, and knowledge management engines.

Develop Innomax IT's AI and GenAI roadmap for GCC clients.

Identify AI use cases for GCCs across shared services, product engineering, finance operations, HR operations, legal operations, procurement, compliance, customer support, analytics, and global delivery.

Design AI architectures using LLMs, RAG pipelines, vector databases, orchestration frameworks, enterprise APIs, data pipelines, cloud platforms, and security layers.

Build GCC-focused AI copilots, enterprise agents, document intelligence tools, knowledge search systems, workflow automation platforms, and decision-support systems.

Create GenAI solutions for productivity improvement, SLA tracking, process automation, knowledge transfer, employee enablement, internal helpdesks, and global delivery governance.

Evaluate and integrate tools such as OpenAI, Anthropic Claude, Azure OpenAI, AWS Bedrock, Google Vertex AI, Hugging Face, LangChain, LlamaIndex, CrewAI, AutoGen, and enterprise vector databases.

Guide teams on prompt engineering, context engineering, AI guardrails, hallucination reduction, responsible AI, model evaluation, LLMOps, and enterprise AI governance.

Work with GCC leaders, transformation heads, technology teams, and business stakeholders to design AI-first operating models.

Support pre-sales, client demos, technical proposals, architecture presentations, and pilot programs for GCC clients.

Build reusable GCC AI accelerators, solution templates, demo environments, and implementation playbooks.

Strong understanding of AI, GenAI, LLMs, RAG, AI agents, NLP, ML, and enterprise AI architecture.

Hands-on experience with Python and modern AI tools/platforms.

Experience with OpenAI, Anthropic Claude, Azure OpenAI, AWS Bedrock, Google Vertex AI, Hugging Face, LangChain, LlamaIndex, or similar tools.

Understanding of enterprise systems, APIs, databases, cloud platforms, security, and data governance.

Ability to design AI solutions for enterprise workflows, shared services, and global delivery environments.

Strong understanding of AI governance, responsible AI, model evaluation, privacy, and security.

Excellent leadership, communication, solutioning, and stakeholder management skills.

Experience working with GCCs, global delivery centres, shared services, consulting firms, or large enterprise transformation programs.

Exposure to AI-led transformation, process automation, enterprise copilots, knowledge management, workflow intelligence, and productivity analytics.

Experience in BFSI, healthcare, life sciences, retail, telecom, manufacturing, or technology GCC environments.

B.Tech / B.E. / M.Tech / MCA / MS / MBA Tech or equivalent qualification.

8–15+ years of technology experience, including 2–4+ years in AI, ML, GenAI, or enterprise AI.

A serious AI builder who understands GCC operations and can convert enterprise problems into production-grade AI solutions. The candidate should think like an architect, execute like a builder, and engage like a transformation leader.

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