Key responsibilities include:

• Driving adoption of Fin by helping prospects unlock the power of our AI capabilities to automate and scale their support operations
• Embedding deeply with strategic customers to understand their business challenges and technical requirements, and providing the insight needed to achieve outstanding results with Fin
• Working hands-on with customers' technical teams as a trusted technical expert, coding side-by-side to drive projects through to completion
• Collaborating closely with Sales, Success, and Product teams to ensure seamless customer experiences, successful project delivery, and actionable product feedback

Requirements include:

• A strong engineering background, preferably in fields such as Computer Science, Mathematics, Software Engineering or Physics
• Experience building a SaaS product with real-world usage
• Strong cross-functional collaboration skills, with the ability to navigate organizational boundaries and bring people together to achieve the best outcomes for our customers and for Intercom
• Proficiency in using and writing REST APIs to integrate systems effectively
• Strong communication skills, with the ability to comfortably discuss technical topics with both engineers and non-technical audiences

Benefits include:

• Competitive salary and equity in a fast-growing start-up
• A well-treated bunch, with awesome benefits!
• Flexible paid time off policy
• Paid maternity leave, as well as 6 weeks paternity leave for fathers
• Comprehensive health and dental insurance for you and your dependents
• Life assurance, as well as a pension scheme & match up to 4%

XML job scraping automation by YubHub

This role sits at the intersection of AI/ML, autonomy, model lifecycle, infrastructure, and product strategy. The PM partners closely with engineering, AI research, Hivemind Solutions, and field teams to deliver the tooling that enables sovereign autonomy, AI Factories at the edge, and continuous learning,capabilities that are central to Shield AI's strategic direction.

This is a high-impact role for an experienced product leader excited to define how foundation models are trained, validated, governed, and deployed across thousands of autonomous systems in highly contested environments.

Responsibilities:

• AI Model Development & Training Platform

Own the roadmap for foundation model training workflows, including dataset ingestion, curation, labeling, synthetic data generation, domain model training, and distillation pipelines. Define requirements for world models, robotics models, and VLA-based training, evaluation, and specialization. Lead the evolution of MLOps capabilities in Forge, including data lineage, experiment tracking, model versioning, and scalable evaluation suites.

• Data, Simulation & Synthetic Data Factory

Define product requirements for synthetic data generation, simulation-integrated data flywheels, and automated scenario generation. Partner with Digital Twin, Simulation, and autonomy teams to convert natural-language mission inputs into data needs, training procedures, and model variants.

• Safe Deployment & Model Governance

Lead the development of model governance and auditability tooling, including model cards, dataset rights, lineage tracking, safety gates, and compliance evidence. Build guardrails and workflows to safely deploy models onto edge hardware in disconnected, GPS- or comms-denied environments. Partner with Safety, Certification, Cyber, and Engineering teams to ensure traceability and evaluation pipelines meet operational and accreditation requirements.

• Edge Deployment & AI Factory Integration

Partner with Pilot, EdgeOS, and hardware teams to integrate foundation-model-based perception and reasoning into autonomy behaviors. Define requirements for distillation, quantization, and inference tooling as part of the “three-computer” development and deployment model. Ensure closed-loop workflows between cloud model training and edge-native execution.

• Cross-Functional Leadership

Collaborate with Engineering, Research, Product, Customer Engagement, and Solutions teams to ensure model outputs meet mission and platform constraints. Translate advanced AI capabilities into intuitive workflows that platform OEMs and partner nations can use to build sovereign AI factories. Sequence foundational capabilities that unblock autonomy, simulation, and customer-facing product teams.

• User & Customer Impact

Develop deep empathy for ML engineers, autonomy developers, and Solutions engineers who rely on the platform. Capture operational data gaps, mission-driven model needs, and domain-specific specialization requirements. Lead demos and onboarding for model-development capabilities across internal and external teams.

XML job scraping automation by YubHub