Strata Control Officer in Bengaluru

About Eudia Eudia is a high-growth AI startup on a mission to transform legal work through Augmented Intelligence—pairing advanced AI with human expertise to supercharge legal teams. Our platform helps Fortune 500 corporate legal departments move faster, manage risk, and transform the legal function from a cost center into a strategic advantage. Eudia is trusted by some of the world’s most demanding organizations, including Cargill, ServiceNow, DHL, Bayer, Duracell, Dolby, Indeed, OpenAI, the U.S. Air Force, Best Buy, Asana, Dropbox, LinkedIn, Citi, Etsy, Novelis, Pure Storage, Del Monte, Cox, PetSmart, Udemy, and many more across regulated and high-stakes industries. Backed by General Catalyst (Hemant Taneja, Marc Bhargava), Floodgate (Mike Maples), Sierra Ventures (Tim Guleri), and leading individual investors including Gokul Rajaram and Prof. Chris Ré (Stanford), Eudia is building deeply technical AI platforms for risk-sensitive environments where accuracy, security, and trust are non-negotiable. We believe the future of legal work lies in AI augmenting human expertise, not replacing it, and we are assembling a world-class team to make that future a reality. About the Role We are looking for a Product Manager to own the end-to-end user experience of Eudia’s core application. This role defines how corporate legal teams interact with AI across workflows such as contract review, diligence, compliance analysis, and advisory research. You will translate powerful AI capabilities into intuitive, trustworthy, and scalable application experiences that align with how legal professionals work. This is a senior role with full ownership of application-layer strategy, workflow design, and enterprise adoption, working closely with AI, platform, design, engineering, and customer teams. What You’ll Own End-to-end product strate

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are You are an experienced Platform Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on. Responsibilities Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC). Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs. Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking. Make and document architectural tradeoffs — partitioning/sharding strat