Jr. AI Native Engineer

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.

We are proud of:

• The work we do and the innovation we drive

• Our values of share, care and dare

• A workplace culture that fosters creativity, diversity and autonomy

• Our borderless, global framework, which enables seamless collaboration

Why Valtech?

At Valtech, we are transforming how people experience the world through technology. Our culture is built around a mindset to make, learn and grow, bringing together technology, creativity and experience to solve meaningful business challenges. [valtech.com]

AI is rapidly changing what it means to build software, and we want people who are excited to be part of that change.

We are looking for an AI Native Engineer who has spent the last few years building strong software engineering foundations while actively exploring what's possible with AI. You are someone who didn't wait for AI to become part of your job description. You started experimenting, building, breaking things and learning.

You may have built an agent because you wanted to understand how agents actually work. You may have experimented with several models to understand their strengths and limitations. Maybe you've created a RAG application, automated part of your development workflow, contributed to an AI project, or simply spent countless hours turning new ideas into working prototypes.

That curiosity matters to us.

If you're an engineer who sees the emergence of AI as an opportunity to fundamentally rethink how software is built, we'd like to meet you.

The role

As an AI Native Engineer, you'll work with multidisciplinary teams to design, prototype and build intelligent digital products and experiences.

You'll combine strong software engineering fundamentals with modern AI capabilities, working across large language models, agentic systems, retrieval, APIs, cloud platforms and emerging development tools.

Importantly, you'll help us discover what's next.

The AI landscape is moving quickly. We don't expect you to have all the answers. We expect you to be excited about finding them.

What you'll do

• Design, build and ship AI-native applications and experiences for real-world use cases.

• Build applications using large language models, generative AI APIs and agentic architectures.

• Develop high-quality software using Python, TypeScript/JavaScript or comparable modern languages.

• Work with models and platforms such as Azure OpenAI, OpenAI, Anthropic Claude, Google Gemini and open-source models.

• Build RAG and knowledge-retrieval solutions using embeddings, semantic search, vector databases and enterprise data.

• Experiment with AI agents, tool/function calling, structured outputs, orchestration and multi-step workflows.

• Integrate AI solutions with APIs, databases, existing platforms and enterprise systems.

• Rapidly prototype new ideas, test assumptions and turn promising experiments into scalable solutions.

• Build approaches for evaluating and testing AI systems, considering quality, accuracy, reliability, latency and cost.

• Use AI-assisted engineering tools to explore new ways of designing, developing, testing and maintaining software.

• Apply sound engineering practices around security, privacy, responsible AI, observability and human oversight.

• Share what you're learning and contribute to the evolving AI engineering practices across Valtech.

What we're looking for

• 2–4 years of professional software engineering or application development experience.

• Strong programming experience with Python, TypeScript/JavaScript or another modern programming language.

• Solid software engineering fundamentals, including application architecture, APIs, testing, debugging, version control and CI/CD.

• Hands-on experience building with generative AI, whether through client work, production applications, prototypes, internal innovation, hackathons, open-source contributions or substantial personal projects.

• Practical experience working with LLMs and model APIs, including prompting, context management, structured outputs and model selection.

• Familiarity with RAG, embeddings, semantic search or vector databases.

• Exposure to agents, function/tool calling or AI workflow orchestration.

• Experience connecting applications to APIs, data sources, databases and cloud services.

• An understanding that building a great AI demo and building a dependable AI product are two very different challenges.

• Most importantly, a demonstrated habit of exploring emerging technology and turning your curiosity into something tangible.

We'd love it if you've...

We don't expect you to check every box. You might have:

• Built your own AI application, agent, copilot or…