Perform code reviews, write automated tests, troubleshoot production issues, and mentor junior engineers.
Participate in architecture discussions and Agile ceremonies.
Use AI-assisted development tools (Gemini, ChatGPT, Cursor, or similar) to improve coding, testing, documentation, and debugging.
Evaluate and integrate AI capabilities into enterprise applications where appropriate.
Leverage LLM APIs, prompt engineering, and AI services to improve business processes and developer productivity.
Collaborate with architects, product owners, QA, and support teams to deliver reliable, high-quality solutions.
Contribute to continuous improvement, engineering standards, and technical documentation, and operational best practices
Stay current with emerging AI technologies and recommend practical adoption opportunities.
Education: Bachelor's degree in Computer Science, Information Technology, Engineering, or related field (or equivalent experience).
Experience: 6+ years building enterprise APIs, microservices, integration platforms, and cloud-native applications with production support experience.
Technical Skills
Strong proficiency in Node.js and TypeScript.
Experience with Kafka (Confluent preferred) and GCP (Cloud Run, Pub/Sub, Cloud Functions, Firestore, Cloud Tasks).
Experience with API Gateways (Gloo/Solo Enterprise preferred)
Knowledge of REST APIs, event-driven architecture, microservices, Docker, Git, GitLab CI/CD, Terraform, ArgoCD, relational and NoSQL databases.
Understanding of secure software development and API management.
Experience using AI-assisted development tools such as GitHub Copilot, ChatGPT, Gemini, Cursor, or similar.
Familiarity with prompt engineering and integrating LLM APIs.
Knowledge of Vertex AI, OpenAI APIs, LangChain, RAG, or AI agents is a plus.
Skills & Competencies
Strong analytical and problem-solving skills.
Excellent communication and collaboration abilities.
Ownership mindset with passion for innovation, AI adoption, and continuous learning.
