Rapidly prototype and deliver POCs and iterate on solutions using an experimentation-driven engineering approach. Design, build, and ship scalable, production-quality features and intelligent services using modern engineering practices. Collaborate across teams to integrate systems, data, and signals into cohesive AI-powered workflows. Debug, troubleshoot, and improve system reliability and performance using telemetry and diagnostics. Build secure, compliant, and responsible AI solutions ready for production scale. Contribute to a culture of continuous learning, experimentation, and engineering excellence. Required (Basic): Bachelor's degree in computer science engineering, or related field 2-5 years of professional software engineering experience with hands-on coding in languages such as C#, Java, Python, or React. Proficiency in AI-native development — working within Agent Harnesses (GitHub Copilot CLI, Coding Agents), authoring Markdown specs/ADRs and YAML configs as Agent-consumable inputs, orchestrating multi-step Agentic workflows across the SDLC, and reviewing Agent-generated code and PRs with production-grade rigor. Strong fundamentals in data structures, algorithms, object-oriented design, and scalable systems. Experience building, testing, debugging, and maintaining production-quality software, following established engineering practices as well as leveraging large language models (LLMs). Solid problem-solving and technical judgment skills, with the ability to design scoped solutions, debug complex issues, and improve service performance. Experience with cloud platforms and distributed/service-oriented architecture. Familiarity with reliability, monitoring, and performance optimization practices. Strong collaboration and communication skills, with experience in design reviews. Passion for building impactful, user-facing AI solutions.
