Assistant General Manager-IT

Role Purpose

We are looking for a hands-on AI Engineering Leader to build and lead the organization's AI & GenAI development capability.

The role will be responsible for designing, developing and deploying AI/GenAI solutions, building a strong AI engineering team, establishing development standards, and converting business opportunities into scalable AI solutions.

The ideal candidate should be technically strong, an experienced Python/AI developer, and capable of leading a team of AI Engineers, Data Engineers and AI/ML specialists.

Experience in Pharmaceutical / Life Sciences / Manufacturing will be preferred.

Key Responsibilities

1. AI & GenAI Development Primary

• Lead the development of enterprise AI, GenAI and Agentic AI solutions.
• Personally contribute to architecture, coding and solution development.
• Develop AI Agents, Copilots, RAG applications and intelligent assistants.
• Build AI solutions using Azure AI Foundry, Azure OpenAI and related Azure AI services.
• Develop Python-based AI applications, APIs and microservices.
• Integrate AI solutions with enterprise applications and data platforms.
• Build reusable AI frameworks, components and accelerators.
• Evaluate and implement emerging AI technologies.

2. AI Engineering Team Leadership

• Build, manage and mentor the AI Engineering team.
• Define team structure, skills, roles and development roadmap.
• Guide engineers on architecture, coding, AI development and deployment practices.
• Conduct technical reviews and ensure engineering quality.
• Establish standards for Git, CI/CD, testing, documentation and production deployment.
• Develop internal AI capabilities and reduce dependency on external vendors.
• Create a culture of innovation, experimentation and rapid prototyping.

3. AI Solution Architecture

• Define architecture for enterprise AI and GenAI solutions.
• Establish standards for:
• RAG
• AI Agents
• LLM integration
• Prompt engineering
• Vector search
• Model evaluation
• AI security
• MLOps
• Design scalable and production-ready AI solutions.
• Ensure AI solutions can integrate securely with enterprise systems.

4. AI Use Case Delivery

• Work with business teams to identify high-value AI opportunities.
• Convert business requirements into AI solution designs and prototypes.
• Lead the complete lifecycle:

Idea PoC Prototype Production Scale

• Prioritize AI use cases based on business value, feasibility and data availability.
• Ensure successful adoption and measurable business outcomes.

5. Data Platform Enablement

• Leverage Snowflake as a key enterprise data foundation for AI.
• Work with Data Engineering teams to ensure availability of high-quality data for AI solutions.
• Utilize Qlik and enterprise analytics as inputs to AI-driven insights and applications.
• Integrate AI solutions with SAP, Salesforce, ServiceNow, manufacturing systems and other enterprise platforms.

6. Stakeholder & Partner Management

• Work closely with business leaders, IT teams and functional stakeholders.
• Translate business problems into practical AI solutions.
• Manage technology partners and AI development vendors where required.
• Present AI roadmap, solutions and progress to senior management.

Must-Have Technical Skills

AI / GenAI

• Generative AI / LLMs
• AI Agent / Agentic AI development
• RAG architecture
• Prompt Engineering
• Vector Databases
• LangChain / LangGraph or equivalent frameworks
• Machine Learning / Predictive Analytics
• AI evaluation and monitoring

Development

• Python – Advanced
• REST APIs
• FastAPI / equivalent
• Git / GitHub
• CI/CD
• Docker / containerization
• Software engineering and coding best practices

Microsoft AI / Cloud

• Azure AI Foundry
• Azure OpenAI
• Azure AI Services
• Azure Cloud
• Azure AI / ML services

Data

• Snowflake
• SQL
• Data pipelines / ETL
• Data modelling
• API-based data integration

Analytics

• Qlik Sense / Qlik
• Advanced Analytics

Preferred Experience

• 10–15+ years of technology / software / data experience.
• 5+ years of hands-on AI/ML/GenAI development experience.
• Experience leading an AI / Data Science / Engineering team.
• Proven experience taking AI solutions from PoC to production.
• Experience building internal AI capabilities rather than only managing vendors.

Pharmaceutical / Life Sciences / Manufacturing experience preferred