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The Technical Project Manager will oversee project lifecycles, manage client relationships, coordinate cross-functionally, and ensure timely delivery of solutions for enterprise clients in the financial services sector.

The role involves owning customer success by translating needs into product workstreams, driving discovery, delivering solutions, and participating in hands-on deployments, focusing on finance and AI integration.

The role involves managing relationships with institutional clients, driving business growth, and building an engagement playbook while promoting AI solutions within financial services.

Own and expand Obin's commercial relationships with flagship insurance clients. Run executive workshops to translate strategic goals into scoped initiatives, drive opportunities to signed funded engagements, represent Obin to C-suite stakeholders, and partner with product, engineering, and delivery teams as the internal voice of the client and insurance industry expert.

Lead the founding platform engineering team to build a secure, auditable AI platform for finance. Own scaffolding, tooling, versioning, gated CI/CD, multi-tenant isolation, compliance harness, testing infrastructure, developer SDKs/APIs, and repeatable vendoring so engineers and customers can safely deploy agent workflows under institutional controls.

Lead end-to-end UX/UI design for AI-first financial products, working with customers, PMs, and engineers. Drive design systems, conduct user research, build prototypes, and champion a high design bar to create intuitive, auditable workflows for regulated institutions.

Lead a team of engineers to build AI platforms for financial services, focusing on best practices, architecture, project delivery, and team growth.

The Full-Stack Engineer will build and scale LLM-based applications, owning technical decisions and ensuring deployment in real customer environments while working directly with the founders and clients in a fast-paced setting.

The Data Scientist will implement, evaluate, and improve LLM-based applications, develop innovative evaluation methods, and streamline investment analytics through AI.

Design and deploy LLM-powered agents, work with clients, maintain production infrastructure, optimize systems, and contribute to platform design.