Develop and operate scalable AI applications from backend logic, prioritizing security and operational excellence.
Apply agentic programming practices to develop new and improved AI-powered features for the application, including refactoring existing codebases to be LLM-based or AI-assisted.
Contribute to technology roadmap discussions to translate business requirements into autonomous, functional solutions.
Write, debug, and troubleshoot code using widely adopted open-source AI technologies and maintain the codebase of a data analysis and validation platform.
Work with cloud-based technologies and solutions.
Capture requirements and refine them within multidisciplinary teams.
Actively tackle problems and set priorities as needed.
Ensure system validation and ongoing application support.
Diagnose and resolve performance issues.
Document code and processes so other developers can easily take over.
Work with teams to integrate our systems with existing internal systems.
Triage product
or system-related issues and debug, track, and resolve problems by analyzing their root causes and their impact on operations and network or service quality.

Bachelor's degree or equivalent experience.
At least five years of experience with Java and Python.
Experience working with agentic frameworks (e.g., ADK, LangChain, LangGraph).
At least five years of experience with API interfaces.
Experience building and using RESTful APIs (assistants interacting with software).
Fundamentals of generative artificial intelligence: understanding how large language models work, including prompt engineering/context engineering.
At least five years of experience with SQL and PostgreSQL.
At least five years of experience with software development management tools like Maven or Gradle and backend technologies such as JAVA/J2EE, Spring Boot, and Microservices.
At least five years of experience implementing software testing, performance, and quality engineering strategies and techniques.
At least three years of experience with cloud technology: Google Cloud Platform.
Familiarity with source control and code assistance systems (e.g., GitHub Copilot, CLI Gemini).
AI evaluation: experience building automated test suites and AI-assisted code refactoring.
Systems thinking: understanding how AI's non-deterministic components integrate into deterministic software systems.
At least one year of experience with Jenkins pipelines.
At least one year of experience designing software with C++.
Proactive, able to prioritize to resolve issues quickly with minimal supervision.
Cloud certification is a strong asset.

Not specified.

AI Engineer

Key skills