Senior Software Engineer

Architect and lead GenAI capabilities for automated test generation, anomaly detection, workflow agents, and ML‑assisted quality insights. Build and integrate AI/ML infrastructure supporting test generation, evaluation harnesses, telemetry‑based observability, and model governance. Optimize models for accuracy, latency, memory, and cost. Drive automation architecture in partnership with automation leads, ensuring AI components work across Desktop, Service, and Semantic Model test frameworks. Collaborate across engineering, PM, and vendor teams to embed AI into release pipelines, improving reliability, flakiness, and regression detection. Mentor engineers in AI concepts, prompt engineering, agent design, and responsible AI practices. Establish metrics and evaluation systems for AI‑powered quality tooling (accuracy, stability, cost, observability). Influence cross‑team direction on secure engineering, CI/CD integration, and pipeline intelligence. Bachelor's or Master's degree in Computer Science, AI, ML, or related field (or equivalent experience) 8+ Strong software engineering skills in Python, TypeScript/JavaScript, C#, or Java. Practical experience building AI/ML powered systems using Azure AI / OpenAI models. Expertise in automation frameworks, CI/CD (Azure DevOps or GitHub Actions), telemetry, and observability. Experience building production AI systems, not just prototypes Ability to design scalable architectures and lead complex technical initiatives. Excellent communication skills and ability to collaborate across global teams. Experience with LLM evaluation, retrieval‑augmented generation, or agent‑based automation. Working knowledge of Power BI, analytics systems, or distributed services. Experience building test frameworks, performance harnesses, or developer tools. Hands-on experience with frameworks such as PyTorch, TensorFlow, or JAX