Product Development Manager

About the role

Job Description: A tech‑savvy product incubation professional who blends strategic product thinking with hands‑on discovery, customer centric and rapid prototyping mindset. You will identify and validate high‑impact opportunities, build prototypes (from low‑ to high‑fidelity), and turn evidence into de‑risked, delivery‑ready bets - often leveraging modern AI/ML where it creates a clear customer and business advantage. Core Responsibilities Discovery & Incubation - Understand and represent the early stages of the Product Lifecycle with Design Thinking in mind. - Lead product discovery to identify customer problems, validate opportunities, and shape product direction before development begins. - Plan and run discovery activities: user interviews, problem‑framing workshops, assumption mapping, journey mapping, and rapid experiments. - Create prototypes from low‑ to high‑fidelity (wireframes, clickable flows, service blueprints) to test desirability, feasibility, and viability. - Synthesize qualitative and quantitative insights into crisp recommendations, hypotheses, and next‑step experiments. - Collaborate closely with Product, Design, Engineering, Data, and Marketing to translate discovery outcomes into actionable delivery plans. - Define and track discovery success metrics to drive learning velocity and evidence‑based decision‑making. - Facilitate alignment across teams by communicating insights, opportunity assessments, and prototype learnings. - Champion a discovery culture - coaching teams on experimentation, user‑centricity, and hypothesis‑driven development. AI/ML‑Fluent Incubation (as relevant to a given concept) - Collaborate with executives, PMs, and stakeholders to prioritize AI initiatives where they create material customer impact. - Lead the design, development, and deployment of AI and UX tools, models, and systems to accelerate validation and pilot outcomes. - Make pragmatic architectural decisions that keep prototypes scalable, efficient, and robust as they move from lab to pilot. - Manage the full AI project lifecycle from research and prototyping to production‑ready handoff and monitoring plans. - Partner with backend/data engineering to productionize ML, including pipelines, feature stores, evaluation, and drift detection. - Mentor teammates and drive innovation by applying current AI research and best practices where they matter. Required Skills & Experience Product Discovery Expertise - Proven experience leading discovery in product‑led organizations. - Strong ability to identify user needs, map journeys, and uncover root problems. - Fluency with Opportunity Solution Trees, Jobs‑to‑Be‑Done, Lean Startup, and Design Thinking. Prototyping & Experimentation - Scale‑up/digital product team experience with fast, iterative cycles. - Proficient with UX tools such as Figma/Sketch (or similar) and rapid prototyping techniques. - Experience designing/running A/B tests, concierge/Wizard‑of‑Oz, smoke tests, and usability tests. - Ability to turn ambiguous ideas into tangible artifacts that drive decisions. Research & Insight Generation - Skilled in user interviews, usability testing, and concept validation. - Able to analyze qualitative and quantitative data; familiarity with analytics tools (Amplitude/Mixpanel/GA) is a plus. Collaboration & Communication - Strong facilitation for workshops, ideation, and alignment. - Clear, concise storytelling to technical and non‑technical audiences; influence without authority across multiple teams. Strategic & Analytical Thinking - Evaluate opportunities based on evidence, business impact, and feasibility. - Structured, hypothesis‑driven problem‑solving; contributes to product strategy and roadmap shaping. AI/ML Engineering Fluency (Hands‑on, T‑shaped) - Strong foundation in Machine Learning & Deep Learning (neural networks, optimization, model evaluation). - Experience delivering enterprise‑grade AI systems and leading cross‑functional AI initiatives. - Practical experience with LLMs/Transformers (e.g., BERT, GPT, LLaMA, Mistral, Claude, Gemini) and prompt/evaluation frameworks. - Proficiency in Python, SQL, LangChain, Hugging Face, and MLOps practices. - Familiarity with Reinforcement Learning and multi‑agent systems for decision‑making in dynamic environments. - Knowledge of multimodal AI (text, image, other modalities) and applied NLP/Text Analytics/Generative AI. - Cloud‑native delivery on Azure (preferred), incl. Databricks, Azure Web Apps, and modern ML pipelines. - Competence in model evaluation & optimization, monitoring, and drift detection, with appreciation for UX principles. Domain Advantage (Big Plus) - Shipping, logistics, and/or supply‑chain management; transportation systems; marketplace/network platforms; exception‑management and real‑time operational decision systems. What You'll Bring (Mindset) - Customer impact over hype; curiosity and hands‑on bias; - balance rigor with pragmatism; - entr