15 hours ago
Responsibilities
- Design, build, and ship AI-native applications and digital experiences.
- Develop applications using large language models, generative AI APIs, and agentic architectures.
- Build RAG and knowledge-retrieval solutions using embeddings, semantic search, vector databases, and enterprise data.
- Experiment with AI agents, tool and function calling, structured outputs, orchestration, and multi-step workflows.
- Integrate AI solutions with APIs, databases, existing platforms, and enterprise systems.
- Prototype ideas rapidly, test assumptions, and turn promising experiments into scalable software.
- Develop evaluation and testing approaches for AI systems based on quality, accuracy, reliability, latency, and cost.
- Apply engineering practices involving security, privacy, responsible AI, observability, and human oversight.
- Share learnings and contribute to Valtech’s evolving AI engineering practices.
Requirements
- 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 through client work, production applications, prototypes, innovation projects, hackathons, open-source contributions, or substantial personal projects.
- Practical experience 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.
- Ability to explore emerging technologies and turn experimentation into tangible applications.
- Preferred experience with Semantic Kernel, LangChain, LangGraph, LlamaIndex, Azure AI Search, Elasticsearch, pgvector, Pinecone, Qdrant, Weaviate, Azure, AWS, Google Cloud, GitHub Copilot, Claude Code, or Cursor.
- Experience building AI applications, agents, copilots, developer tools, RAG solutions, multi-agent workflows, or AI output evaluations is valued.
Benefits
- Continuous learning, experimentation, and professional growth opportunities.
- Collaboration with engineering, data, experience, and strategy teams on meaningful client and business challenges.
- Opportunities to work with emerging AI capabilities and help shape AI-native engineering practices at Valtech.
- A global, borderless framework supporting collaboration across locations.
- A workplace culture focused on making, learning, growing, creativity, diversity, autonomy, and shared learning.
Tech Stack
Categories
About Valtech
Valtech provides digital consulting and engineering services to large enterprises, delivering customer experience design, commerce platforms, data/AI solutions, and transformation programs. It works across sectors such as retail, financial services, manufacturing, mobility, health, and travel, offering strategy, design, build, and managed services. Founded in 1993, Valtech is a global company privately held under Kharis Capital.