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Ferrovial

Global operator of sustainable transportation infrastructure

Digital Product Builder - AI-Native

AI Application EngineeringPosted on Nov 10
Full-timeAustin, TX, USANo salary listed

About the Job

Requirements

  • Two to five years of experience in software development, product engineering, solutions engineering, or a closely related role.
  • Demonstrated experience delivering digital solutions end-to-end, from prototype through MVP and iteration.
  • Strong software engineering fundamentals, including APIs, version control, debugging, testing, and basic system design.
  • Hands-on experience using AI tools to accelerate development, such as LLM copilots, coding agents, or 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.

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, including 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, such as adoption, time saved, error reduction, and 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 technical and non-technical audiences.
  • Contribute reusable patterns, templates, and best practices for AI-native product development.

Desired Qualifications

  • Experience with agentic AI patterns, multi-step workflows, retrieval-augmented generation (RAG), or LLM evaluation and observability.
  • Proficiency in one or more programming languages such as Python, JavaScript/TypeScript, C#, or SQL.
  • Familiarity with modern web or backend frameworks and cloud environments; Azure is 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.

About the Company

Ferrovial

Global operator of sustainable transportation infrastructure

Ferrovial operates globally in the infrastructure sector, focusing on transportation, and handles engineering, construction, and long-term operation of assets like toll roads and airports. It often delivers projects through public-private partnerships, earning revenue from construction contracts and concessions. The company stands out due to its global footprint and emphasis on sustainability, integrating project delivery with asset management. Its goal is to develop, build, and manage sustainable infrastructure that serves public needs over the long term.

Company size
10,001+
Company stage
IPO
Headquarters
Madrid, Spain
Founded
1952

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