AI Project Manager

Mployee.me; Delhi; Presencial; INR 1 800 000 - 3 000 000; Tempo integral

Resumo da oferta

Mployee.me in India seeks an AI-focused Project Manager to drive strategic AI initiatives, oversee end-to-end automation, and align roadmaps with business goals. You will bridge business leadership, technical teams, and external vendors to deliver measurable ROI and high adoption of automated tools across units.

Ideal candidates bring 5–9 years in AI deployment, strong experience with workflow platforms, and the ability to translate complex concepts into actionable plans.

Qualificações

• 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.

Responsabilidades

• AI Strategy & Roadmap Development: Define and execute a phased, high-impact AI roadmap aligned with business objectives across departments.
• Workflow Automation: Design end-to-end automation workflows integrating existing enterprise apps.
• Vibe Coding & Prototyping: Lead rapid prototyping and translate business pain points into system requirements.
• ROI Analytics: Build financial models and monthly dashboards tracking ROI performance.
• Vendor & Stakeholder Management: Manage external AI software vendors and communicate with executives.
• Engineering Oversight: Collaborate with engineering to maintain delivery momentum and platform architecture.

Conhecimentos

AI deployment experience

Workflow automation

Agile/Scrum/Hybrid

Cloud orchestration

ROI modeling

Formação académica

Bachelor's or Master's degree in CS/IT/Business or analytical engineering

Ferramentas

n8n

Make

Zapier

Power Automate

Descrição da oferta de emprego

JOB DESCRIPTION: Project Manager – AI

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

AI Strategy & Roadmap Development

• 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.

ROI Analytics & Financial Case Development

• 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, Client & Management Communication

• 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.
• Technical Foundation: Maintain a functional, operational literacy in database structures (MySQL, PostgreSQL, NoSQL architectures) and foundational programming frameworks (Python, JavaScript, REST APIs, JSON data maps) to effectively guide core product decisions.

Team Leadership & Personnel Management

• 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

• AI Strategy & Roadmap Design
• Executive-Level Communication
• Workflow Automation Platforms
• Team Building & Mentorship
• ROI Modeling & Financial Analysis
• Vendor & Stakeholder Management
• AI Platform Architecture
• Change Management & Empathy
• Vibe Coding & Low-Code Deployment
• Strategic Thinking
• Business Requirements Analysis
• Conflict Resolution
• Database & API Knowledge
• Decision-Making Under Uncertainty
• Data Governance & AI Ethics
• Cross-Functional Collaboration

4. Work Environment & Corporate Culture

• 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.