Junior AI Native Engineer

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

📋 Description

• Design, develop, and launch AI-native applications and solutions tailored for real-world applications.

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

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

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

• Develop RAG and knowledge-retrieval systems 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.

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

• Establish methods for assessing and testing AI systems regarding quality, accuracy, reliability, latency, and cost.

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

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

• Share insights and contribute to the advancement of AI engineering practices across Valtech.

• Collaborate with diverse 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.

• Practical experience in building applications with generative AI.

• Hands-on experience with LLMs and model APIs, focusing on 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 connecting applications to APIs, data sources, databases, and cloud services.

• Understanding of the distinction between AI demonstrations and reliable AI products.

• Proven inclination to explore emerging technologies and convert curiosity into tangible outcomes.

🏝️ Benefits

• Opportunities for continuous learning.

• Professional development opportunities.

• A workplace culture that promotes creativity, diversity, and autonomy.

• A borderless, global framework that enables seamless collaboration.

• Opportunities to apply cutting-edge AI capabilities to impactful client and business challenges.

• Space to innovate, learn, and grow.