AI Technical Project Manager

Promaynov Advisory Services Pvt. Ltd; Delhi; On-site; INR 3,000,000 - 4,500,000; Full time

Job summary

Promaynov Advisory Services Pvt. Ltd seeks an experienced AI Technical Project Manager to lead end-to-end planning and delivery of enterprise AI initiatives across Generative AI, Agentic AI, workflow automation and AI-enabled business solutions.

You will coordinate across business, AI engineering, data, security and platform teams, manage risks and governance, and ensure solutions scale from prototype to production, while aligning with enterprise requirements for security and architecture.

Responsibilities

• Lead End-to-End AI Solution Delivery
• Own delivery planning and execution across AI initiatives from discovery, experimentation and PoC through MVP/Beta, production rollout and subsequent scaling, establishing clear milestones, outcomes and delivery accountability.
• Work closely with AI Engineers, Solution Architects, Data teams and platform teams to manage dependencies across LLMs, RAG pipelines, agentic frameworks, APIs, cloud infrastructure, enterprise applications and data sources, proactively identifying and resolving delivery blockers.
• Bring together Business SMEs, Product/BA, UX, AI Engineering, Architecture, Security, Risk and Platform teams, ensuring decisions, actions and ownership are clearly defined and delivery remains aligned to business priorities.
• Manage
• Coordinate architecture reviews, security assessments, model-risk/governance requirements, data/privacy controls, testing, operational readiness and production approvals to ensure AI solutions meet required enterprise standards.
• Maintain integrated delivery plans, RAID management, resource requirements, budgets and inter- project dependencies, while providing concise progress, risks and decision requirements to SteerCo, senior stakeholders and accountable executives.
• Establish a delivery approach that supports rapid AI experimentation without compromising production controls, helping teams prioritise use cases, validate value early, manage transition from prototype to production and reuse common AI platforms, patterns and capabilities

Job description

We are looking for an experienced AI Technical Project Manager to lead the end-to-end planning and delivery of enterprise AI initiatives across a portfolio of Generative AI, Agentic AI, workflow automation and AI-enabled business solutions. The role will work at the intersection of business, AI engineering, architecture, data, security and enterprise platforms, ensuring AI solutions progress from experimentation and prototype through production deployment, adoption and scale. The individual should have sufficient technical understanding of LLMs, RAG, agentic workflows, APIs, cloud platforms and enterprise integrations to effectively manage technical dependencies, challenge delivery plans and facilitate decisions across multidisciplinary teams. The role will coordinate multiple AI use cases and stakeholders, establish clear delivery governance, manage risks and dependencies, and ensure solutions meet enterprise requirements for security, architecture, model governance and production readiness.

Responsibilities

• Lead End-to-End AI Solution Delivery
• Own delivery planning and execution across AI initiatives from discovery, experimentation and PoC through MVP/Beta, production rollout and subsequent scaling, establishing clear milestones, outcomes and delivery accountability.
• Work closely with AI Engineers, Solution Architects, Data teams and platform teams to manage dependencies across LLMs, RAG pipelines, agentic frameworks, APIs, cloud infrastructure, enterprise applications and data sources, proactively identifying and resolving delivery blockers.
• Bring together Business SMEs, Product/BA, UX, AI Engineering, Architecture, Security, Risk and Platform teams, ensuring decisions, actions and ownership are clearly defined and delivery remains aligned to business priorities.
• Manage
• Coordinate architecture reviews, security assessments, model-risk/governance requirements, data/privacy controls, testing, operational readiness and production approvals to ensure AI solutions meet required enterprise standards.
• Maintain integrated delivery plans, RAID management, resource requirements, budgets and inter- project dependencies, while providing concise progress, risks and decision requirements to SteerCo, senior stakeholders and accountable executives.
• Establish a delivery approach that supports rapid AI experimentation without compromising production controls, helping teams prioritise use cases, validate value early, manage transition from prototype to production and reuse common AI platforms, patterns and capabilities