AI Project Director

post-implementation quality parameters and verified employee satisfaction indexes.\n\n2. Core Responsibilities\nAI Strategy & Roadmap Development\nHigh-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.\nPrioritization: Assess and prioritize technical initiatives based on operational feasibility, pipeline impact, and financial ROI potential.\nMarket Awareness: Monitor global technology shifts, benchmark competitor ecosystems, and deliver a quarterly 'State of AI' landscape report to the executive leadership team.\n\nWorkflow Automation & Platform Architecture\nSystem Integration: Design and oversee end-to-end automation workflows that integrate smoothly with existing enterprise applications (CRM, HRMS, Legacy Databases, etc.).\nPlatform Mastery: Demonstrate strong hands-on mastery of modern enterprise workflow tools such as n8n, Make, Zapier, or Microsoft Power Automate.\nGovernance & Compliance: Establish robust AI governance, data privacy parameters, continuous model-monitoring controls, and ethical compliance frameworks from day one.\nBuild vs. Buy Analysis: Evaluate complex commercial build vs.

buy solutions with structured technical and financial risk analysis.\n\nVibe Coding, Prototyping & Technical Translation\nRapid 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.\nDiscovery Engineering: Lead discovery workshops with business heads to translate practical pain points into crisp system requirements, user stories, and precise technical briefs.\nQuality Assurance Check: Evaluate early low-code/vibe-coded prototypes for production readiness before passing them to core developer lines.\n\nROI Analytics & Financial Case Development\nFinancial Modeling: Build data-grounded financial models projecting cost optimizations, capacity release, and structural quality returns to capture leadership approval.\nKPI Dashboards: Monitor and distribute detailed monthly dashboards reporting target vs. actual ROI performance benchmarks.\n\nVendor, Client & Management Communication\nVendor Optimization: Serve as the master point of contact for external AI software companies, SaaS vendors, and specialized system integrators; negotiate precise SLAs.\nExecutive Advisory: Translate complex, multi-layered algorithmic and machine learning engineering terms into simplified, accessible strategic vocabulary for non-technical stakeholders.\nCulture Catalyst: Champion a data-driven, AI-first work culture through internal continuous learning series, lunch-and-learn presentations, and proactive change management strategies.\n\nEngineering Oversight & Architecture (Added Advantage)\nVelocity Protection: Partner directly with engineering lines, data scientists, and DevOps specialists to break execution blockers and maintain delivery timeline momentum.\nTechnical 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.\n\nTeam Leadership & Personnel Management\nCross-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.\nPsychological Safety: Construct a highly collaborative, innovative, and safe team environment that incentivizes experimentation, speed, and learning from failure.\nResource Optimization: Control tactical resource allocation patterns to avoid personnel burnout while defending roadmap velocity commitments.\n\n3. Qualifications & Competencies\nRequired Qualifications\nEducation: Bachelor's or Master's university degree in Computer Science, Information Technology, Business Administration, or a heavily analytical engineering field.\nProfessional 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.\nDelivery 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.\nIntegration Literacy: Verifiable hands-on track record using cloud workflow orchestration engines (n8n, Make, Zapier, or Power Automate).\nCommercial Competence: Documented background creating financial case summaries, tracking cost-mitigation parameters, and proving tech investments ROI.\n\nPreferred Capabilities / Added Advantage\nProgramming Baseline: Functional literacy or script reading skill in Python, JavaScript, and advanced SQL querying mechanisms.\nML/LLM Knowledge: Working familiarity with basic machine learning models, fine-tuning structures, vector search, and model APIs (OpenAI, Anthropic, Gemini).\nPrototyping Frameworks: Familiarity using advanced code assistant tools (Cursor, Replit, v0.dev, Copilot).\nCertifications: Active industry credentials (PMP, PMI-ACP, PRINCE2) or specialized vendor certifications from AWS, Microsoft, Google, or DeepLearning.AI.\n\nTechnical Competencies\nLeadership Competencies\nAI Strategy & Roadmap Design\nExecutive-Level Communication\nWorkflow Automation Platforms\nTeam Building & Mentorship\nROI Modeling & Financial Analysis\nVendor & Stakeholder Management\nAI Platform Architecture\nChange Management & Empathy\nVibe Coding & Low-Code Deployment\nStrategic Thinking\nBusiness Requirements Analysis\nConflict Resolution\nDatabase & API Knowledge\nDecision-Making Under Uncertainty\nData Governance & AI Ethics\nCross-Functional Collaboration\n\n4.

Work Environment & Corporate Culture\nAI-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.\nHigh 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.\nInnovation Incubator: Personnel are consistently encouraged, measured, and expected to proactively test, pilot, and pitch novel AI-augmented infrastructure solutions directly to executive directors.\nRigorous 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.