Jobs at Obin AI

Own the platform product roadmap for APIs, SDKs, MCP and A2A protocol integrations. Define developer experience strategy, partner with engineering on architecture and versioning, and create documentation, sample code, reference architectures, and technical content. Lead developer relations through workshops, talks, demos, and community engagement. Establish developer experience metrics, promote reusable blueprints, and build the platform and developer relations function from an early stage.

Own product strategy and execution for an AI platform serving regulated financial institutions. Lead customer discovery, roadmap development, AI product trade-offs, domain-expert translation, and iterative delivery. Build and lead the product organization while personally contributing to specifications, discovery, and edge-case analysis. Operate as a business leader responsible for adoption, revenue, unit economics, customer relationships, and investor-facing product representation.

Own enterprise financial services accounts end to end, including stakeholder relationships, opportunity qualification, ROI validation, deal scoping, pricing, closing, renewals, expansions, QBRs, and delivery handoffs. Navigate regulated risk, legal, procurement, and security reviews while partnering with presales, engineering, product, and delivery teams. The role requires insurance industry knowledge, quota or renewal ownership, technical fluency, and strong executive communication.

Originate and close new-logo enterprise sales with banks, insurers, asset managers, and alternative managers. Build target-account strategies, conduct outbound prospecting, navigate complex buying committees, qualify opportunities using MEDDPICC, construct commercial proposals, negotiate seven- and eight-figure deals, and hand off signed scopes to delivery teams. The role requires personally carrying and achieving quota, selling into financial institutions, and creating credibility for an early-stage AI company.

Own Obin AI’s enterprise B2B positioning, messaging, competitive intelligence, sales enablement, launches, case studies, demos, and commercial packaging. The role requires translating technical agentic AI capabilities into credible narratives for regulated financial institutions. This hands-on position includes building messaging architecture, leading a Series A announcement, creating customer proof programs, developing battlecards, ensuring claim discipline, and connecting product releases to enablement. The successful candidate brings enterprise positioning experience, financial services fluency, strong writing skills, technical comfort, and end-to-end launch ownership.

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.

Serve as the first sales engineer, partnering with Client Partners and Account Executives throughout discovery, demonstrations, architecture, security reviews, scoping, and delivery handoff. Lead technical discovery, explain AI accuracy and evaluation methods, address model risk and compliance concerns, scope opportunities with engineering, and create reusable enablement materials. Build the technical sales function, demo assets, discovery framework, objection library, and technical sales processes for regulated financial-services clients.

Build and lead production-grade agentic AI systems for regulated financial institutions. Responsibilities include setting AI governance and evaluation standards, designing LLM and RAG agents, owning backend infrastructure and APIs, optimizing reliability and performance, partnering with customers, shaping platform architecture, and mentoring engineers. The role requires extensive software engineering and AI/ML experience, strong Python and cloud infrastructure skills, and expertise in multi-agent orchestration, safety, and system evaluation.

Build and scale production LLM-powered agents and RAG systems for regulated financial workflows. Responsibilities include designing agent orchestration, backend infrastructure, APIs, evaluation and optimization frameworks, observability, and reusable AI platforms. The role involves direct customer collaboration, technical architecture ownership, and establishing engineering standards. Candidates should bring substantial software engineering experience, production experience with AI agents, Python expertise, cloud infrastructure knowledge, and strong systems architecture and communication skills.

Build and deploy production-grade LLM-powered agents and RAG systems for regulated financial workflows. Responsibilities include designing agent orchestration, owning backend infrastructure and APIs, evaluating accuracy and reliability, optimizing performance and cost, establishing AI safety standards, shaping platform architecture, partnering with customers, and mentoring engineers. The role also contributes to technical strategy, engineering culture, hiring standards, and long-term product direction.

Design enterprise multi-cloud architectures and agentic AI platforms for regulated financial institutions. Build multi-agent workflows, RAG systems, voice agents, streaming AI applications, and vector database routing. Architect Kubernetes-based infrastructure across GCP, AWS, and Azure using Terraform, while supporting Spark and Airflow data pipelines, BigQuery, Snowflake, and governed data ecosystems. Lead technical advocacy, publish reusable architectures, and align research, engineering, and executive stakeholders.

Own full-cycle recruiting for technical, AI/ML, engineering, product, and GTM roles during a 6–12 month engagement. Responsibilities include developing sourcing strategies, mapping talent markets, partnering with hiring leaders, managing candidate processes, maintaining pipeline data, negotiating offers, improving interview processes, and advising on AI/ML hiring trends and compensation. This hands-on individual contributor role requires strong technical recruiting expertise, stakeholder influence, operational rigor, and candidate experience focus.

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.

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

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 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.