Valtech - Jr. AI Native Engineer

• Build applications using large language models, generative AI APIs and agentic architectures. • large language models, generative AI APIs and agentic architectures • Develop high-quality software using Python, TypeScript/JavaScript or comparable modern languages. • 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. • 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. • RAG and knowledge-retrieval solutions • Experiment with AI agents, tool/function calling, structured outputs, orchestration and multi-step workflows. • 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. • evaluating and testing AI systems • Use AI-assisted engineering tools to explore new ways of designing, developing, testing and maintaining software. • security, privacy, responsible AI, observability and human oversight • 2–4 years of professional software engineering or application development experience. • 2–4 years of professional software engineering or application development experience • Strong programming experience with Python, TypeScript/JavaScript or another modern programming language. • 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. • Hands-on experience building with generative AI • Practical experience working with LLMs and model APIs, including prompting, context management, structured outputs and model selection. • LLMs and model APIs • Familiarity with RAG, embeddings, semantic search or vector databases. • RAG, embeddings, semantic search or vector databases • Exposure to agents, function/tool calling or AI workflow orchestration. • 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. • 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 developer tool. • AI application, agent, copilot or developer tool • Experimented with multiple models and learned where each performs well, and where it doesn't. • Built RAG solutions using real-world or enterprise data. • Explored agentic architectures, tool use or multi-agent workflows. • Worked with frameworks such as Semantic Kernel, LangChain, LangGraph or LlamaIndex. • Semantic Kernel, LangChain, LangGraph or LlamaIndex • Used technologies such as Azure AI Search, Elasticsearch, pgvector, Pinecone, Qdrant or Weaviate. • Azure AI Search, Elasticsearch, pgvector, Pinecone, Qdrant or Weaviate • Built applications on Azure, AWS or Google Cloud. • Azure, AWS or Google Cloud • Used tools such as GitHub Copilot, Claude Code or Cursor as part of your engineering workflow. • GitHub Copilot, Claude Code or Cursor • Created evaluations or testing approaches for AI outputs. • Participated in AI hackathons, internal innovation initiatives or open-source communities. • Seen a newly released AI capability and thought,“I need to try that.” • “I need to try that.” • Specific frameworks will come and go. We're more interested in how you learn, what you've built and what you've discovered along the way. • how you learn, what you've built and what you've discovered along the way. • You are • A builder.You don't just read about AI. You build with it. You're comfortable moving from an idea to a prototype and learning through experimentation. • A builder. • An explorer.New models, multimodal experiences, agents, reasoning systems and AI development tools genuinely interest you. You're energized by a technology landscape where the playbook is still being written. • An explorer. • An engineer.You care about what happens after the demo. Reliability, maintainability, architecture, security and testing matter to you. • An engineer. • A pragmatic thinker.You understand that AI isn't the answer to every problem. You're interested in finding where it creates genuine value, not adding AI for AI's sake. • A pragmatic thinker. • A learner.You won't know every new model, framework or technique. That's okay. What matters is being able to say:“I haven't worked with that yet. Let's figure it out.” • A learner. • “I haven't worked with that yet. Let's figure it out.” • What you can expect from us • You'll join an environment where experimentation and continuous learning are part of how we work. You'll collaborate with people across engineering, data, experience and strategy, and have opportunities to apply emerging AI capabilities to meaningful client and business challenges. • Valtech currently recruits across AI-focused roles alongside engineering, cloud, data and digital experience disciplines, reinforcing that AI is being embedded within the broader technology organization rather than existing solely as a standalone specialty. • You'll have room to make, learn and grow, while helping shape what AI-native engineering means at Valtech. • make, learn and grow