Applied AI Lead

Alternative Payments • New York, NY

2d • Hybrid

About The Position

Alternative Payments is building the financial operating system for SMBs, consolidating the disconnected tech stack that holds service-based businesses back. Starting with MSPs, we've spent five years perfecting accounts receivable, and we're now expanding into accounts payable, AI-powered analytics, and beyond. We're at an inflection point: closing the loop on money movement and laying the foundation for a platform that will reshape how service businesses operate financially.
We're growing fast, thinking big, and building a global team that wants to be part of something that lasts. We believe the best solutions come from diverse perspectives, deep collaboration, and a shared obsession with customer impact. If you're energized by real problems, real customers, and real impact, we want to hear from you!
We’re seeking an Applied AI Lead to join our team and own the AI layer powering our internal operations.
This is not a typical AI role. You’ll work alongside our bizops, finance, support and engineering teams to identify where AI can eliminate manual work, reduce cycle time and surface better decisions. You’ll also serve as the technical guardrail for AI work happening across the company, setting the architecture, security standards and integration patterns that let teams build with confidence.
This role is ideal for someone who thrives on technical problem-solving with real business context, and wants to take a hands-on role in shaping how an AI-native fintech platform gets built from the inside out.
This role is available to candidates eligible to work in the US, hybrid in New York.

Requirements

• 6+ years of operating experience in biz ops, strategy, transformation, consulting, software development, data or a similar outcome-owning role with meaningful depth in AI systems: you’ve built and shipped production AI, not just used it.
• Production prompt engineering and context engineering experience: You can articulate the trade-offs between long context, RAG, fine-tuning, and tool use, and have made these calls before.
• MCP experience: you've built MCP servers, integrated them into agent workflows, and understand the design space.
• Strong understanding of AI security: prompt injection, access control in agentic systems, data exposure risks, and how to harden LLM-adjacent infrastructure.
• The ability to move fluidly between product technical and operational/biz-ops contexts: translating AI capabilities into business outcomes and vice versa.
• Strong communication skills to explain complex AI tradeoffs to non-technical stakeholders and earn trust across teams without formal authority.
• A proactive mindset with the ability to drive projects independently in a high-ambiguity, fast-moving environment.

Nice To Haves

• Background in fintech, payments, or a data-rich vertical SaaS environment.
• Familiarity with operational engineering or internal tooling contexts, not just external product surfaces.
• Experience evaluating or improving AI systems built by teams without deep AI expertise.
• Comfort working in fast-paced, high-ownership environments where the architecture is still being defined.

Responsibilities

• Act as the operational owner of AI at the business; partner with functional leaders to identify high-leverage areas where AI tooling can dramatically reduce effort, increase quality, or accelerate timelines
• Stand up agentic workflows end-to-end using Claude Code (or similarly capable models), our internal stack, MCPs, etc.
• Own context engineering, prompt design, tool definitions, eval harnesses, and human-in-the-loop checkpoints.
• Build and maintain reusable skills, sub-agents, and MCP integrations that compound across functions
• Own AP's internal AI tool stack: model selection, vendor evaluation, build-vs-buy decisions, license utilization, data handling policies, and access controls.
• Support the biz-ops and operational engineering team in building AI-native dashboards and workflows that are architected for scale.
• Act as a resource on AI security across the organization: prompt injection defense, access controls in agentic systems, vulnerability assessment, and staying current on emerging AI attack surfaces.
• Collaborate with the Head of Data to ensure data infrastructure supports AI consumption patterns and advocate for what needs to change to unlock specific product bets.
• Help raise AI literacy across the organization and facilitate training sessions.
• Support product organization on AI feature implementation: define context structure, retrieval strategy, and how agents interact with platform data.
• Propose and help establish AI best practices, tooling standards, and evaluation frameworks across both product and operational contexts.

Benefits

• Competitive salary tailored to your experience, skills, and expertise.
• The base salary for this role is $150K–$200K. The range displayed on each job posting reflects the approximate total target compensation for the position. Within the range, individual pay is determined by factors including relevant skills, experience, education/training.
• Equity opportunities so you can share in our growth and success.
• Unlimited PTO and flexibility when you need it the most.
• Yearly learning & development stipend to help you grow and do your best work.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed