Senior Product Manager, AI Product/Design Lead – Supply Chain/Logistics
We are looking for a hands‑on, AI‑native Product Manager (Product Manager 2.0) to lead the evolution of IFS.ai Logistics as we move to an agent‑first, AI‑native product operating model.
- Full-time
- IFS Referral Bonus Code: SH
- Job Location: Hybrid
Product Area: IFS.ai Logistics
Location: London / UK (Office based or Hybrid)
Reporting to: VP Optimization & Simulation
Role Summary
We are looking for a hands‑on, AI‑native Product Manager (Product Manager 2.0) to lead the evolution of IFS.ai Logistics as we move to an agent‑first, AI‑native product operating model.
This is not a traditional “requirements writer” or coordination role.
You will:
- Own product definition and delivery for AI‑driven optimization capabilities
- Work directly with customers to explore and validate logistics decision‑making workflows
- Personally craft prototypes, simulations, and experiments to shape product direction
- Actively push engineering teams to deliver high‑quality, trustworthy, production‑ready AI systems
You are expected to build, test, and learn, not just direct.
You will use modern AI tooling to collapse the gap between idea and learning within the IFS.ai Logistics portfolio.
This includes:
- Rapid prototyping using tools such as Replit
- Creating lightweight working demos and agent behaviour experiments
- Using these artefacts to:
- Validate logistics workflows with customers
- Explore agent decision‑making, failure modes, and trust
- Reduce risk before engineering investment
You do not need to be an engineer — but you must be hands‑on and comfortable producing real artefacts that engineers can build from.
- Lead discovery for agent‑based and AI‑first capabilities within IFS.ai Logistics
- Work hands‑on with:
- LLM‑powered planning and decision workflows
- Agent interactions, escalation paths, and human‑in‑the‑loop controls
- Simulation and synthetic data as discovery and validation tools
- Use prototypes and experiments to answer questions such as:
- What decisions should the agent take vs. the user?
- Where is explainability mandatory?
- What does “trust” mean in a logistics planning context?
Roadmapping, Delivery & Engineering Quality
- Own outcome‑oriented roadmaps for IFS.ai Logistics capabilities
- Connect:
- Customer value
- Commercial priorities
- Platform and AI strategy
- Use discovery artefacts (prototypes, simulations, experiments) to:
- Justify roadmap decisions
- Align stakeholders
- Push for the right solutions, not just faster delivery
- Act as a strong partner — and challenger — to engineering:
- Raise the bar on quality, usability, and system behaviour
- Ensure AI features are production‑grade, not experimental
What Success Looks Like (6–12 Months)
- IFS.ai Logistics roadmaps are:
- Outcome‑driven
- Credible
- Clearly connected to customer problems
- Prototypes are routinely used to:
- Validate ideas early
- Reduce delivery risk
- Improve engineering focus
- Engineering teams feel:
- Challenged
- Aligned
- Supported by clear product direction
- Customers trust and adopt AI‑enabled logistics capabilities
Why IFS.ai Logistics
IFS.ai Logistics combines AI, simulation, and optimisation to support complex logistics and supply‑chain decision‑making at scale.
This role sits at the heart of that ambition — shaping how AI‑native products are discovered, designed, and delivered across the IFS portfolio.
Product Management Basics
- 5+ years experience in software product management role
- Strong experience road‑mapping and managing prioritisation within resource constraints
- B2B or Enterprise SaaS product management is essential
- Logistics/supply chain industry experience is essential
- Proven experience personally prototyping product ideas
- Comfortable using AI tools to explore and validate concepts
- Strong bias toward learning by making
- Able to translate rough prototypes into clear product direction
- Comfortable engaging deeply with engineers on technical trade‑offs
- Uses data and artefacts — not opinions — to drive decisions
- Willing to push teams toward higher standards, not lowest‑effort delivery
AI & Technical Fluency
- AI‑native mindset with practical understanding of:
- Agents
- LLM‑based workflows
- System limitations and failure modes
- Not a data scientist — but technically credible with AI and engineering teams
We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles, while also valuing inclusive workplace experiences. By fostering a sense of community, we drive innovation, strengthen connections, and nurture belonging. Our commitment ensures you can work in a way that suits you best, while also engaging with colleagues to share ideas and build meaningful relationships.
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