Technical Product Manager

Own and drive the end-to-end lifecycle of AI- and data-intensive technical initiatives across multiple products. Define and evolve data management strategy , including data modeling standards, pipeline requirements, governance, lineage, and quality frameworks. Lead product strategy for agentic systems , including orchestration layers, tool usage patterns, memory/context management, guardrails, and fallback strategies. Establish and operationalize evaluation frameworks for AI products (LLM evals, benchmarking, human-in-the-loop review, automated scoring, drift monitoring). Partner with engineering to design scalable architectures that support data ingestion, transformation, context retrieval, and multi-agent coordination. Translate business objectives into clear technical specifications spanning APIs, data contracts, orchestration logic, and observability requirements. Define metrics for success across system performance, data quality, model reliability, latency, cost optimization, and user outcomes. Identify and mitigate risks across model behavior, data integrity, security, and compliance. Oversee validation processes for AI systems, including regression testing, prompt versioning, evaluation harnesses, and continuous improvement loops. Act as a bridge between product, data engineering, ML engineering, and platform teams to ensure technical alignment and delivery excellence. Communicate roadmap progress, architectural trade-offs, and performance insights to executive stakeholders with clarity and rigor. Foster a culture of accountability, structured experimentation, and high technical standards across teams.