We are:

Wizeline, a global AI-centric technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact.

With the right people and the right ideas, there’s no limit to what we can achieve

Are you a fit?

Sounds awesome, right? Now, let’s make sure you’re a good fit for the role:

Responsibilities:

- Acting as the technical and client-facing lead of the AI Impact Squad.
- Building trusted relationships with engineering teams, business stakeholders and subject-matter experts.
- Proactively identifying problems and opportunities rather than waiting for fully defined requirements.
- Leading discovery to understand business processes, user needs, technical systems, operational constraints and risk considerations.
- Translating ambiguous business problems into clear technical hypotheses, solution options and delivery plans.
- Determining when AI is appropriate, when conventional software is more suitable and when a combined approach is required.
- Providing technical direction, delivery structure and day-to-day support to the L4 engineer.
- Remaining hands-on across architecture, prototyping, implementation, integration, testing and production rollout.
- Connecting technical delivery to measurable business, operational or engineering outcomes.
- Communicating clearly with both technical and non-technical stakeholders throughout the engagement.
- Conduct workshops, interviews and working sessions with stakeholders and SMEs to understand how existing processes and systems operate.
- Identify bottlenecks, repetitive work,



decision points and opportunities where software or AI could create meaningful impact.
- Convert loosely defined challenges into clear problem statements, hypotheses, use cases and success criteria.
- Explore the problem before committing to a solution, including validating assumptions, analysing workflows and understanding available data and systems.
- Design and build production-grade applications, services and workflows that incorporate LLMs, agents, retrieval, automation or conventional software components.
- Build rapid prototypes to validate feasibility, user value and technical risk before scaling.
- Define the architecture, interfaces, integration approach and engineering standards for each initiative.

Must-have Skills To be successful in this role, you must have:

- Strong professional experience as a software engineer, including the design and delivery of production systems.
- Hands-on experience building applications or workflows using LLMs, generative AI or agentic systems.
- Strong software engineering fundamentals, including system design, APIs, testing, observability, security and maintainability.
- Experience working directly with stakeholders, users or clients to understand problems and shape solutions.
- Ability to operate effectively when requirements are incomplete, unclear or still evolving.
- Strong product and business judgement,



with the ability to connect technical decisions to user and organisational outcomes.
- Ability to independently lead discovery, define scope and drive an initiative from an initial idea through production delivery.
- Experience designing and integrating AI-enabled capabilities into existing software platforms and business workflows.
- Practical understanding of LLM evaluation, prompt and context design, retrieval, tool use, agents, guardrails and human-in-the-loop workflows.
- Ability to assess whether AI is the right solution rather than applying it by default.
- Experience leading or mentoring other engineers and providing technical direction within a small team.
- Strong communication skills and the ability to explain technical concepts, trade-offs and risks to non-technical stakeholders.
- Comfortable challenging assumptions, influencing decisions and creating structure within ambiguous environments.
- Outcome-driven and pragmatic, with a preference for delivering useful working systems over producing theoretical recommendations.

Nice to have:

- Experience in banking, payments, fintech or another regulated environment is highly valuable.
- Exposure to Azure, .NET or Azure DevOps is advantageous but is not a hard requirement.

What we offer:

- Competitive compensation & total rewards
- Health benefits & wellness programs
- Savings & retirement plans
- Global mobility opportunities
- Versátil work policy and remote-friendly approach
- Happy hours, gaming tournaments, sports activities & more
- Continuous learning & training programs with WizeAcademy
- Free certifications in cloud technologies and coding languages

Find out more about our culture here .

📌 AI Staff Software Engineer (España)
🏢 Wizeline
📍 España