AI Project Manager

Techmagnate -
Delhi, Delhi

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Job details

Full-time
4 hours ago

Qualifications

Cloud infrastructure
Azure
Computer Science
PMP
Relational databases
Software deployment
Enterprise Software
NoSQL
Git
Research
MongoDB
PMI-ACP
Master's degree
Databases
SQL
AWS
Project management
Bachelor's degree
Machine learning
JavaScript
PostgreSQL
Requirements analysis
REST
Scrum
GitHub
APIs
Project management methodology
Agile
Business Administration
JSON
Business requirements
AI
Leadership
Python
MySQL
Information Technology
PRINCE2 Certification

Full job description

Project Manager – Artificial Intelligence | Job Description CONFIDENTIAL

JOB DESCRIPTION

Project Manager – AI

ROLE OVERVIEW

The Project Manager – Artificial Intelligence (AI-PM) is a strategic and execution-focused role responsible for
leading the company's AI transformation journey. This individual will drive automation across every
department, aligning AI initiatives with business objectives to save time, reduce costs, and significantly
improve quality of output.

The AI-PM will bridge the gap between business leadership, technical teams, and external vendors —
translating complex AI capabilities into tangible, measurable outcomes for the organisation.

POSITION DETAILS

Position Title Project Manager – Artificial Intelligence (AI-PM)

Department Technology / Digital Transformation

Reports To Chief Technology Officer (CTO) / CEO

Employment Type Full-Time

Experience Required 5–9 Years (AI / Digital Transformation Projects)

Location On-Site

STRATEGIC OBJECTIVE

Enable company-wide automation by identifying, planning, and delivering AI-powered solutions across all
departments — achieving measurable gains in operational efficiency and output quality.

Key Success Metrics

Reduction in manual processing time per department
Positive ROI achieved within defined project timelines
Adoption rate of AI tools across all business units
Quality improvement scores pre-implementation vs. post-implementation
Number of successful AI deployments per quarter

Project Manager – Artificial Intelligence | Job Description CONFIDENTIAL

Employee satisfaction and time saved through automation

KEY ROLES & RESPONSIBILITIES

1. AI Strategy & Roadmap Development

Define and maintain a comprehensive AI roadmap fully aligned to the company's business objectives

and departmental needs.

Identify automation opportunities across Finance, HR, Operations, Sales, Marketing, and Customer

Support.

Prioritise AI initiatives based on business impact, feasibility, and ROI potential.
Develop phased implementation plans with clear milestones, timelines, and measurable success

criteria.

Stay ahead of market trends and translate emerging AI opportunities into actionable strategies.
Present AI strategy updates to leadership on a regular cadence.

2. Workflow Platform Management

Demonstrate strong hands-on knowledge of workflow automation platforms such as n8n, Make, Zapier,

Microsoft Power Automate, or equivalent tools.

Design and oversee end-to-end automation workflows that integrate seamlessly with existing business

systems (CRM, HRMS, etc.).

Evaluate and recommend the most suitable platforms based on scalability, cost-efficiency, and

business needs.

Ensure automation workflows are properly maintained, monitored, and continuously optimised for

performance.

Document all workflows with clear SOPs and handover guides for operational teams.

3. ROI Calculation & Business Case Development

Build detailed ROI models for proposed AI projects, including cost savings, time reduction, and quality

improvement projections.

Track and report on actual vs. projected ROI post-implementation across all active AI initiatives.
Develop compelling business cases to secure leadership buy-in and budget approvals.
Define KPIs and measurement frameworks for every AI initiative and report performance monthly.
Benchmark AI investment returns against industry standards and competitor data.

4. Designing Effective AI-Driven Platforms

Architect scalable, user-friendly, and operationally integrated AI-driven platforms for enterprise use.
Establish AI governance frameworks including data quality standards, model monitoring protocols, and

ethical AI usage guidelines.

Ensure platforms incorporate feedback loops for continuous learning, model retraining, and

performance improvement.

Design with security, privacy, regulatory compliance, and data governance requirements built in from

day one.

Evaluate build vs. buy decisions for AI tools and platforms with clear technical and commercial

justifications.

5. Articulating & Evangelising 'Why AI'

Clearly articulate the strategic value and business case for AI adoption to non-technical stakeholders in

accessible language.

Project Manager – Artificial Intelligence | Job Description CONFIDENTIAL

Educate internal teams and management on AI benefits, limitations, risks, and realistic implementation

expectations.

Champion a data-driven, AI-first culture across the organisation through workshops, lunch-and-learns,

and internal communications.

Address change management challenges and resistance to AI adoption proactively through empathy

and evidence.

Produce internal thought leadership content to build organisational AI literacy.

6. Research, Innovation & Market Awareness

Continuously research the latest AI tools, frameworks, large language models (LLMs), and

industry-specific AI applications.

Monitor competitor AI adoption and identify best practices from global industry leaders for potential

adoption.

Evaluate emerging technologies and present structured findings and recommendations to leadership

regularly.

Actively engage with AI communities, conferences, webinars, and research papers; maintain a strong

professional network.

Deliver a quarterly 'State of AI' report covering technology trends, vendor landscape, and strategic

recommendations.

7. Vibe Coding & Low-Code / No-Code AI Development

Demonstrate practical knowledge of vibe coding — using AI-assisted coding tools (Cursor, Replit AI,

GitHub Copilot, v0, etc.) with natural language prompts to rapidly prototype solutions.

Leverage low-code/no-code platforms and AI-augmented development to accelerate solution delivery

without full engineering dependency.

Bridge the gap between business requirements and technical implementation using AI-augmented

development approaches.

Evaluate vibe-coded prototypes for production-readiness and escalate appropriately to the engineering

team.

Maintain awareness of the capabilities and limitations of AI code generation tools to guide responsible

adoption.

8. Business Requirement Analysis & Product Translation

Conduct structured discovery sessions with department heads to deeply understand pain points,

inefficiencies, and strategic objectives.

Translate business requirements into detailed product specifications, user stories, process flows, and

technical briefs.

Facilitate workshops to map current-state processes and co-design AI-powered future-state workflows

with stakeholders.

Validate that all delivered AI solutions accurately and completely address the original business

requirements.

Maintain a centralised requirements repository ensuring full traceability from requirement through to

delivery and sign-off.

9. Client & Vendor Communication

Serve as the primary point of contact for all external AI vendors, SaaS providers, and technology

partners.

Negotiate contracts, SLAs, and deliverables with vendors; manage vendor performance throughout the

full engagement lifecycle.

Communicate project status, risks, changes, and outcomes to clients and internal stakeholders through

regular structured updates.

Project Manager – Artificial Intelligence | Job Description CONFIDENTIAL

Manage expectations proactively and resolve conflicts between business needs and technical

constraints diplomatically.

Prepare and deliver polished executive-level presentations, live demo sessions, and formal project

review reports.

10. Technical Implementation Oversight (Added Advantage)

Oversee and review technical implementations to ensure alignment with architectural decisions, quality

standards, and delivery timelines.

Conduct or facilitate code reviews and technical walkthroughs in collaboration with the engineering

team when required.

Collaborate closely with developers, data scientists, and DevOps engineers to remove blockers and

maintain delivery velocity.

Understand API integrations, webhook configurations, and system architecture at a functional level to

guide technical decision-making.

11. Technical Foundations – Database & Coding Literacy

Maintain working knowledge of relational databases (MySQL, PostgreSQL) and NoSQL systems

(MongoDB, Firebase) to support AI data pipelines.

Understand fundamental programming concepts in Python, JavaScript, or similar languages to

communicate effectively with technical teams.

Ability to read and interpret code, SQL queries, and data schemas without needing to write production

code independently.

Familiar with REST APIs, JSON data formats, and core cloud infrastructure concepts (AWS, Azure,

GCP).

12. Team Leadership & Management

Build, mentor, and manage a cross-functional AI project team including developers, data analysts, UX

designers, and QA engineers.

Define clear roles, responsibilities, and performance expectations for all team members.
Foster a collaborative, innovative, and psychologically safe team environment that encourages

experimentation.

Conduct regular 1:1s, performance reviews, and provide constructive and timely feedback.
Resolve team conflicts and maintain high team morale, engagement, and productivity throughout the

project lifecycle.

Plan resource allocation and manage workload distribution proactively to prevent burnout and delivery

risk.

13. Management Communication & Alignment

Maintain a regular communication cadence with C-suite and senior leadership on AI project status,

risks, and opportunities.

Translate complex technical AI concepts into clear, strategic business language for non-technical

executives.

Present monthly and quarterly project dashboards showing progress against KPIs, delivery milestones,

and ROI metrics.

Proactively surface risks, blockers, and dependencies to management alongside recommended

mitigations and contingency plans.

Align AI project priorities with evolving company strategy and business direction during leadership

planning cycles.

Project Manager – Artificial Intelligence | Job Description CONFIDENTIAL

QUALIFICATIONS & EXPERIENCE

Required Qualifications

Bachelor's or master’s degree in computer science, Information Technology, Business Administration,

or a related field.

5–9 years of project management experience, with at least 3 years focused on AI, automation, or

digital transformation.

Proven track record of delivering AI projects end-to-end from ideation through to production

deployment.

Hands-on experience with Agile, Scrum, or hybrid project management methodologies.
Strong proficiency in workflow automation platforms (n8n, Make, Zapier, Power Automate, or similar).
Demonstrated ability to calculate, present, and track ROI for technology investments.

Preferred / Added Advantage

Hands-on experience with Python, JavaScript, or SQL for technical communication and oversight.
Familiarity with machine learning concepts, LLMs, and AI APIs (OpenAI, Anthropic, Google Gemini,

etc.).

Experience with vibe coding tools such as Cursor, Replit, v0.dev, or GitHub Copilot.
PMP, PMI-ACP, PRINCE2, or equivalent project management certification.
AI/ML certifications from Google, AWS, Microsoft, or DeepLearning.AI.
Experience with enterprise software integration, ERP systems, or large-scale SaaS implementations.

CORE COMPETENCIES

TECHNICAL COMPETENCIES LEADERSHIP COMPETENCIES

AI Strategy & Roadmap Design Executive-Level Communication

Workflow Automation Platforms Team Building & Mentorship

ROI Modelling & Financial Analysis Vendor & Stakeholder Management

AI Platform Architecture Change Management

Vibe Coding & Low-Code Development Strategic Thinking

Business Requirements Analysis Conflict Resolution

Database & API Knowledge Decision Making Under Uncertainty

Research & Technology Evaluation Cross-Functional Collaboration

Data Governance & AI Ethics Client Relationship Management

WORK ENVIRONMENT & CULTURE

Project Manager – Artificial Intelligence | Job Description CONFIDENTIAL

AI-First Culture You will work in and help shape an organisation that believes
automation and AI are core competitive advantages.

High Impact Role Direct influence on company-wide productivity, profitability, and
digital capability.

Innovation Driven Encouraged to experiment, prototype, and pitch new AI tools and
ideas on a regular basis.

Data Informed All decisions are backed by data. You will have access to analytics
and dashboards to guide priorities.

Collaborative Work alongside leadership, cross-functional teams, clients, and
leading technology vendors.

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