Junior AI Native Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and deploy AI-native applications and experiences tailored for real-world scenarios.

• Create applications utilizing large language models, generative AI APIs, and agentic architectures.

• Produce high-quality software using Python, TypeScript/JavaScript, or other contemporary programming languages.

• Collaborate with Azure OpenAI, OpenAI, Anthropic Claude, Google Gemini, and open-source models.

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

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

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

• Rapidly prototype concepts, validate assumptions, and transform experiments into scalable solutions.

• Develop methods for assessing and testing AI systems for quality, accuracy, reliability, latency, and cost-effectiveness.

• Utilize AI-assisted engineering tools throughout software design, development, testing, and maintenance.

• Implement practices for security, privacy, responsible AI, observability, and human oversight.

• Share knowledge and contribute to the advancement of Valtech’s AI engineering methodologies.

• Collaborate with interdisciplinary teams across engineering, data, experience, and strategy.

⛳️ Requirements

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

• Proficient programming skills in Python, TypeScript/JavaScript, or another modern programming language.

• Strong foundation in software engineering principles, including application architecture, APIs, testing, debugging, version control, and CI/CD.

• Hands-on experience with generative AI technologies.

• Practical knowledge of 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 invocation, or AI workflow orchestration.

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

• Proven track record of exploring emerging technologies and turning curiosity into practical applications.

• Understanding of reliability, maintainability, architecture, security, and testing for dependable AI products.

🏝️ Benefits

• Continuous opportunities for learning and professional development.

• Chance to leverage emerging AI technologies to address significant client and business challenges.

• Collaborative environment across engineering, data, experience, and strategy.

• Global, borderless workplace framework that promotes seamless collaboration.

• Workplace culture that nurtures creativity, diversity, and autonomy.