Digital Product Builder (AI-Native)

Ferrovial•Austin, TX

1d•Hybrid

About The Position

Ferrovial is expanding its AI-enabled digital delivery capabilities to accelerate product development and process transformation across its business units and corporate functions. This is a hands-on builder role where the Digital Product Builder (AI-Native) will translate business needs into working prototypes and MVPs, iterate quickly with stakeholders, and help scale successful solutions in partnership with Engineering, AI, and UX teams. Success in this role is measured by real adoption and measurable business impact.

Requirements

2–5 years of experience in software development, product engineering, solutions engineering, or a closely related role.
Demonstrated experience delivering digital solutions end-to-end (prototype to MVP to iteration).
Strong fundamentals in software engineering, including APIs, version control, debugging, testing, and basic system design.
Hands-on experience using AI tools to accelerate development (e.g., LLM copilots, coding agents, prompt-driven workflows).
Ability to write clear technical and functional documentation, including user stories, acceptance criteria, and workflow definitions.
Strong communication skills and comfort working directly with business stakeholders.

Nice To Haves

Experience with agentic AI patterns, multi-step workflows, RAG, or LLM evaluation and observability.
Proficiency in one or more languages such as Python, JavaScript/TypeScript, C#, or SQL.
Familiarity with modern web or backend frameworks and cloud environments (Azure preferred).
Exposure to CI/CD pipelines, containerization, or production monitoring tools.
Experience delivering automation or AI-enabled solutions in an enterprise environment.
Interest in infrastructure, construction, energy, transportation, or corporate digital transformation.

Responsibilities

Partner with business stakeholders to understand workflows, pain points, constraints, and value drivers.
Identify high-impact opportunities where AI, automation, and digital products can improve efficiency, quality, cost, risk, and user experience.
Translate ambiguous business needs into clear problem statements, user stories, and acceptance criteria.
Rapidly build prototypes, proofs of concept, and MVPs using AI-assisted coding tools and agentic workflows (e.g., coding agents, prompt-driven development, automated testing and documentation).
Create clear specifications, prompts, and agent instructions that enable AI systems (and engineering partners) to generate maintainable, production-ready code.
Iterate quickly based on user feedback, usage data, and stakeholder input.
Own delivery from discovery through MVP and iteration, ensuring solutions are usable, reliable, and fit for real-world use.
Collaborate with Engineering and AI teams to harden successful prototypes into scalable, secure, and supportable solutions when required.
Define lightweight success metrics (adoption, time saved, error reduction, throughput improvements) and track outcomes.
Support or build integrations with enterprise systems and data sources using APIs, data pipelines, and automation tools.
Operate within enterprise standards for security, data handling, compliance, and reliability.
Work closely with UX, product, and business teams to ensure solutions align with real user workflows.
Clearly communicate tradeoffs, risks, and recommendations to both technical and non-technical audiences.
Contribute reusable patterns, templates, and best practices for AI-native product development.