AI Project Manager

Techmagnate - A Digital Marketing Agency; New Delhi; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Techmagnate - A Digital Marketing Agency in Delhi seeks an AI Product Manager (AI-PM) to lead the company’s AI transformation journey. This role bridges business leadership, technical teams, and external vendors to deploy enterprise-wide automation, reduce costs, and improve output quality.

You will drive rapid prototyping, discovery workshops, and governance frameworks while coordinating with Finance, HR, Operations, Marketing, and Customer Support to ensure measurable ROI.

Qualifications

• Education: Bachelor's or Master's in Computer Science, Information Technology, Business Administration, or analytical engineering field.
• 5-9 years of project management with 3+ years in AI deployment and enterprise-scale digital transformations.
• Delivery: end-to-end portfolio tracking and Agile/Scrum/hybrid methods.
• Integration: hands-on with cloud workflow engines (n8n, Make, Zapier, Power Automate).
• Commercial: experience building financial cases and ROI tracking.

Responsibilities

• Define and execute a phased AI roadmap aligned with business objectives across functions.
• Prioritize initiatives based on feasibility, ROI, and impact.
• Produce quarterly 'State of AI' reports for executives.
• Oversee end-to-end automation workflows and platform governance.
• Translate complex ML concepts into actionable requirements for non-technical stakeholders.

Skills

Executive Leadership

AI Strategy

Workflow Automation

Vendor Management

Stakeholder Mgmt

Agile/Scrum

Data Governance

Communication

Education

Bachelor's/Master's in CS/IT/Eng

MBA preferred

Tools

n8n

Make

Zapier

Power Automate

Job description

Enterprise Technology & Digital Transformation Lifecycle

Strategic Objective

The AI-PM is a strategic, execution-focused leader driving the company's AI transformation journey. This individual bridges the gap between business leadership, technical teams, and external vendors to deploy company-wide automation, save time, reduce costs, and dramatically improve organizational output quality.

Key Success Metrics

• Processing & Time Savings: Measurable reduction in manual processing time per department and total corporate hours saved.
• Financial Impact: Positive, systematically tracked ROI achieved within defined product and project timelines.
• Adoption & Velocity: High active adoption rates of automated tools across business units and consistent quarterly AI deployments.
• Quality & Satisfaction: Improved pre- vs. post-implementation quality parameters and verified employee satisfaction indexes.

2. Core Responsibilities

• High-Impact Strategy: Define and execute a phased, high-impact AI roadmap aligned with overarching business objectives across Finance, HR, Operations, Sales, Marketing, and Customer Support.
• Prioritization: Assess and prioritize technical initiatives based on operational feasibility, pipeline impact, and financial ROI potential.
• Market Awareness: Monitor global technology shifts, benchmark competitor ecosystems, and deliver a quarterly 'State of AI' landscape report to the executive leadership team.

Workflow Automation & Platform Architecture

• System Integration: Design and oversee end-to-end automation workflows that integrate smoothly with existing enterprise applications (CRM, HRMS, Legacy Databases, etc.).
• Platform Mastery: Demonstrate strong hands-on mastery of modern enterprise workflow tools such as n8n, Make, Zapier, or Microsoft Power Automate.
• Governance & Compliance: Establish robust AI governance, data privacy parameters, continuous model-monitoring controls, and ethical compliance frameworks from day one.
• Build vs. Buy Analysis: Evaluate complex commercial build vs. buy solutions with structured technical and financial risk analysis.

Vibe Coding, Prototyping & Technical Translation

• Rapid Prototyping: Utilize 'vibe coding' principles using natural language inside AI development shells (Cursor, Replit AI, GitHub Copilot, v0) to accelerate prototype deployment without engineering bottlenecks.
• Discovery Engineering: Lead discovery workshops with business heads to translate practical pain points into crisp system requirements, user stories, and precise technical briefs.
• Quality Assurance Check: Evaluate early low-code/vibe-coded prototypes for production readiness before passing them to core developer lines.
• Financial Modeling: Build data-grounded financial models projecting cost optimizations, capacity release, and structural quality returns to capture leadership approval.
• KPI Dashboards: Monitor and distribute detailed monthly dashboards reporting target vs. actual ROI performance benchmarks.
• Vendor Optimization: Serve as the master point of contact for external AI software companies, SaaS vendors, and specialized system integrators; negotiate precise SLAs.
• Executive Advisory: Translate complex, multi-layered algorithmic and machine learning engineering terms into simplified, accessible strategic vocabulary for non-technical stakeholders.
• Culture Catalyst: Champion a data-driven, AI-first work culture through internal continuous learning series, lunch-and-learn presentations, and proactive change management strategies.

Engineering Oversight & Architecture (Added Advantage)

• Velocity Protection: Partner directly with engineering lines, data scientists, and DevOps specialists to break execution blockers and maintain delivery timeline momentum.
• Cross-Functional Operations: Directly coordinate, mentor, and track performance across a cross-functional Agile unit comprising developers, data analysts, system architects, UI/UX engineers, and QA assets.
• Psychological Safety: Construct a highly collaborative, innovative, and safe team environment that incentivizes experimentation, speed, and learning from failure.
• Resource Optimization: Control tactical resource allocation patterns to avoid personnel burnout while defending roadmap velocity commitments.

3. Qualifications & Competencies

Required Qualifications

• Education: Bachelor's or Master's university degree in Computer Science, Information Technology, Business Administration, or a heavily analytical engineering field.
• Professional Background: 5-9 years of structural project management experience, with a validated minimum of 3 years strictly dedicated to AI deployment, complex workflow automation, or enterprise-scale digital transformations.
• Delivery Execution: Proven, end-to-end portfolio tracking product evolution from conceptual design phase through to live enterprise rollout using Agile, Scrum, or hybrid workflow methods.
• Integration Literacy: Verifiable hands-on track record using cloud workflow orchestration engines (n8n, Make, Zapier, or Power Automate).
• Commercial Competence: Documented background creating financial case summaries, tracking cost-mitigation parameters, and proving tech investments ROI.

Core Competency Matrix

• Executive-Level Communication
• Workflow Automation Platforms
• Change Management & Empathy
• Vibe Coding & Low-Code Deployment
• Strategic Thinking
• Business Requirements Analysis
• Database & API Knowledge
• Decision-Making Under Uncertainty
• Data Governance & AI Ethics
• Cross-Functional Collaboration
• AI-First Mindset: We operate in an aggressive, progressive corporate landscape where internal workflow automation and AI scaling are resourced as primary, non-negotiable competitive business advantages.
• High Market Impact: This position holds deep strategic authority with real-time, measurable influence over company-wide profit sheets, employee operational capacity, and structural framework maturity.
• Innovation Incubator: Personnel are consistently encouraged, measured, and expected to proactively test, pilot, and pitch novel AI-augmented infrastructure solutions directly to executive directors.
• Rigorous Data Foundations: All operational paths and tool deployment architectures are cleanly metrics-driven. You will operate with open access to precise data analytics layers and performance dashboards to direct strategic priorities.