Top Tech Jobs & Startup Jobs

Build and evaluate LLM-based agentic applications for regulated financial workflows. Responsibilities include developing evaluation methods, optimizing prompts and contexts, conducting applied and exploratory AI research, integrating models and proprietary data, designing AI-native systems, and applying statistics and machine learning to investment processes such as sourcing, screening, due diligence, and asset monitoring.

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.