Define and own the technical strategy, architecture, and roadmap for AI/ML and GenAI platforms.
Lead hands‑on development and optimization of LLM‑based solutions, including prompt engineering, prompt chaining, and inference workflows.
Design and implement GenAI evaluation and benchmarking frameworks (accuracy, relevance, hallucination, safety, regression).
Apply strong data science fundamentals to define metrics, KPIs, experimentation approaches, and model validation strategies.
Architect and scale GCP‑based AI/ML solutions, ensuring performance, security, cost optimization, and production readiness.
Collaborate with Data Engineering, Product, QA, DevOps, and Business teams to onboard and scale AI use cases.
Establish standards for AI quality, governance, explainability, and responsible AI practices.
Mentor AI/ML engineers and data scientists, driving technical excellence and consistency across teams.
Required Qualifications
8 - 12+ years of experience in AI/ML engineering, data science, or applied ML platform development, including technical leadership roles.
Strong hands‑on experience with LLMs, prompt engineering, and GenAI solution design.
Solid background in data science, including statistics, NLP, ML algorithms, and model evaluation techniques.
Proven experience building cloud‑native AI/ML solutions on GCP (e.g., BigQuery, Cloud Storage, Cloud Run/Compute, IAM, managed AI services).
Strong Python skills and experience leading or reviewing production‑grade AI/ML code.
Ability to clearly communicate complex technical concepts and trade‑offs to senior technical and business stakeholders..