Applied AI Lead

🕒 May 7

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Alternative Payments

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

💳 Fintech

🤝 B2B

🛍️ eCommerce

Fintech • B2B • eCommerce

Alternative Payments is a payment processing platform specifically designed for service-based businesses. It streamlines customer payment processing, enhances collections, and offers financing options, enabling businesses to unify their invoicing and payment solutions seamlessly. The platform includes security features to safeguard transactions and provides automation tools to reduce administrative efforts. With Alternative Payments, businesses can improve revenue flow and enhance the customer payment experience, ensuring that payments are completed quickly and efficiently.

📋 Description

• 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.

🎯 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.

🏖️ Benefits

• Competitive salary tailored to your experience, skills, and expertise. • 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.