Principal Product Manager

Organization Background We are a technology-driven organization focused on building enterprise-scale platforms across Software Engineering and AI Engineering . Our mission is to accelerate innovation by embedding AI capabilities (GenAI, Agentic AI, automation) directly into core software engineering workflows and developer platforms . We prioritize production-grade, scalable, and secure systems over experimentation, ensuring all solutions are governed, observable, cost-efficient, and aligned to real business outcomes . Our platforms enable end-to-end delivery across both: Software Development Lifecycle (SDLC) AI Development Lifecycle (AIDLC) What Will You Be Responsible For Own the product strategy and roadmap for platforms spanning: Software Engineering (APIs, microservices, DevOps, IDP) AI Engineering (AIDLC, LLM platforms, agentic systems) Drive convergence of SDLC + AIDLC , ensuring AI becomes a native part of engineering systems , not an isolated layer Lead productization of: AI-powered developer platforms (copilots, automation agents) Reusable APIs, SDKs, and platform services Ensure end-to-end lifecycle ownership : Software: design → build → deploy → operate AI: data → model → evaluate → deploy → monitor Define and track engineering + AI metrics : DORA metrics (deployment frequency, MTTR) AI metrics (accuracy, latency, cost, automation %) Partner with Engineering, AI/ML, DevOps, and Security teams to ensure: Reliability, scalability, and governance at enterprise scale What Would Your Day Look Like Working with engineering teams on: API design, microservices scalability, platform architecture decisions Collaborating with AI/ML teams on: RAG pipelines, agent workflows, model evaluation strategies Reviewing production telemetry across both systems : Software: latency, error rates, service health AI: token usage, hallucination rates, drift, cost Driving backlog prioritization balancing: Feature velocity vs platform stability vs AI innovation Leading trade-off discussions: Build vs buy (platform vs vendor tools) Model choice vs cost vs latency Standardization vs team flexibility Ensuring: AI systems are integrated into CI/CD pipelines Software systems are AI-enabled where it adds real value Handling real-world production issues: Service failures and cascading microservice dependencies AI degradation (drift, poor retrieval, inaccurate outputs) Cost spikes due to scale or inefficient AI usage This role operates at the intersection of platform engineering, AI systems, and production reliability . Who Are We Looking For A Product Manager with strong experience in: Software Engineering platforms (APIs, microservices, DevOps) AI/ML systems (LLMs, RAG, agentic workflows, AIDLC) Deep understanding of: Distributed systems, cloud-native architectures, and SDLC End-to-end AIDLC (data → model → evaluation → deployment → monitoring) Someone who: Thinks in platforms (reusability, scalability) , not features Prioritizes production readiness over demos Challenges assumptions and drives data-backed decisions Proven ability to: Deliver 0 → 1 → scale platforms in enterprise environments Balance engineering rigor with AI innovation Strong focus on: Reliability, cost control, governance, and measurable outcomes