Founding Engineer, Applied AI

Caraa; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

Caraa is looking for a Founding Engineer to lead their New York Applied AI team. This role will involve building agentic systems and applied AI workflows, taking ownership of critical systems, and working closely with senior leadership. You'll be instrumental in shaping the future of operational efficiency and automation.

The ideal candidate should have over 6 years of production software experience, fluency in AI frameworks, and the ability to mentor engineers. Join Caraa at the forefront of AI integration in the financial space.

Qualifications

• 6+ years in production software with end-to-end ownership and delivery.
• Deep understanding of AI tools and frameworks.
• Strong skills across frontend and backend technologies.

Responsibilities

• Own applied AI workflows from design to production.
• Identify and replace workflows with automation.
• Mentor new team members and elevate engineering standards.

Skills

Production software development

AI fluency with frameworks

Full-stack development

System design for real-world state

Mentoring and technical direction

Strong communication skills

Job description

About Pockyt

Pockyt is building the AI-native infrastructure for global money movement. We give merchants a single platform to accept payments from anywhere, send money globally, and manage funds through Global Virtual Accounts and stablecoins — but our ambition runs deeper than the rails themselves. We're architecting the connective tissue that lets money move across borders the way information moves across the internet: instantly, intelligently, and autonomously.

We serve a wide spectrum of merchants, from sophisticated enterprise platforms running complex multi-currency operations to the next generation of AI-powered startups, including the one-person unicorns we believe are about to reshape the global economy. Today, that means one integration, one account view, and one place to track everything. Tomorrow, it means a financial layer that AI agents can natively transact on — where money flows are orchestrated, optimized, and reconciled without human bottlenecks.

Our mission is to make global commerce frictionless. We're not building another payments platform. We're building the operating system for how value moves in an agentic, borderless economy.

The Role

We're hiring a Founding Engineer to start our New York Applied AI team — the small, senior, AI-leveraged group whose mandate is to compress quarters into days across Pockyt. This is our second engineering hire and our first engineering leadership hire in NYC. You'll set the bar for who joins next and lay down the patterns a 20x engineering org will inherit.

Your charter is agentic systems and applied AI, deployed wherever the highest-leverage workflow lives. The work begins inside the company because that's where the friction is most visible and the wins are most measurable — manual payment processing, compliance reviews, RFI loops, merchant onboarding, settlement reconciliation, treasury operations, and merchant configuration are full of workflows waiting to be replaced with agents. But the work doesn't stay there. The patterns you prove on our own operations are the same patterns we expose to merchants as Pockyt becomes the financial layer AI agents transact on. What you build here becomes the substrate.

This is a founder-mode builder-leader role. You'll own critical systems end-to-end, lead technical discovery on ambiguous problems, set the standards the engineers behind you will inherit, and mentor the team as it grows. You'll report directly to our CEO and collaborate closely with our Head of Product and the other technical leaders driving execution — Head of Product Engineering, Head of Engineering Operations, and Chief Architect — on system design, rollout, and how this team plugs into the rest of engineering.

If you've been waiting for the role where you get to build the self-improving company — instrument it, automate it, and watch the feedback loops compound until they reach the merchant — this is it.

What You'll Do

• Own the applied AI and agentic workflow surface end-to-end: discovery, design, prototyping, production rollout, measurement, and iteration
• Embed with Finance, Compliance, Ops, GTM, Support — and increasingly with merchants — to identify the workflows with the highest leverage and replace them with agents and software: reconciliation, KYC/EDD review queues, RFI triage, payment initiation, merchant configuration, reporting pipelines
• Build durable, observable agentic systems: LLM-orchestrated workflows with retries, evals, rollback, and instrumentation that survive contact with real money movement
• Graduate the highest-leverage workflows into merchant-facing product capability — the agent that reconciles our books becomes the agent merchants run on theirs
• Set the technical foundation the broader Applied AI org will build on — eval frameworks, agent guardrails, prompt and tool design conventions, shared SDKs (some of which become merchant-facing), and observability standards
• Mentor and pair with the engineers who join behind you; raise the bar on code review, testing, and shipping discipline; help interview, hire, and onboard each new team member
• Partner with the Chief Architect on guardrails for AI-generated code and agent-executed actions touching ledgers, settlements, and customer funds
• Define success metrics for every system you ship — hours saved, manual payments eliminated, time-to-resolution, error rates, merchant time-to-value — and own the outcome publicly
• Translate ambiguous executive asks into shipped systems; close the loop by demoing what's live and what's next

What We're Looking For

• 6+ years building production software, with a clear track record of owning critical systems end-to-end and shipping outcomes — not just features
• Deep AI fluency — you use Claude, Cursor, Codex, and LLM/agent frameworks (LangGraph, Inngest, Temporal, browser automation, eval tooling, etc.) as a daily force multiplier and have opinions about when each one helps
• Strong full-stack instincts across TypeScript and Python, with comfort moving across frontend, backend, data plumbing, and integrations; depth in one area is fine, rigidity in only one is not
• Experience designing agentic or workflow systems that touch real-world state (payments, ledgers, customer data) with safety, idempotency, observability, and rollback as first-class concerns
• A history of operating without a backlog — you spot the problem, scope it, ship it, measure it, and move on
• Demonstrated ability to mentor, set technical direction, and elevate the engineers around you; you’ve been the person whose patterns the rest of the team copies
• Excellent written and verbal communication — you'll present to executives weekly and write specs and post-mortems for non-engineers
• Genuine curiosity about how the business actually runs, and the patience to sit with ops, finance, and compliance to understand the workflow before automating it

Bonus Points

• Prior experience as an early or founding engineer at a fast-moving startup, or as the technical lead for a forward-deployed / applied AI / platform team
• Experience in fintech, cross-border payments, digital wallets, merchant acquiring, treasury, or financial reconciliation
• Background in RegTech, compliance automation, KYC/KYB workflows, or transaction monitoring
• Hands-on experience building eval pipelines and regression tests for LLM systems in production
• Track record of recruiting and hiring engineers into a small, senior, AI-native team

Why Pockyt

• Build at the frontier of AI + payments at a company shipping for both enterprise platforms and the next generation of AI-native merchants
• Real ownership and direct work with senior leadership from day one — and a leading hand in building the team ...
• A clear path into engineering ...

How You'll Work

• Rhythm: Rapid ideation → scoped prototype (hours/days) → pilot → production hardening → measure and iterate; weekly executive demos
• Collaboration: Daily collaboration with product, design, ops, finance, and compliance stakeholders; close partnership with Chief Architect on guardrails and Head of Product Engineering on rollout
• Quality bar: Ship small, safe, observable changes with clear rollback; instrument every workflow with outcome metrics; build evals before you scale anything LLM-driven
• Team building: Set the hiring bar, run technical interviews, and onboard the engineers who join behind you

Success looks like: measurable elimination of manual hours across Finance, Compliance, and Ops in your first quarter; a documented library of agents and workflow patterns the rest of the company builds on; the first systems you ship graduating into merchant-facing capability; a clear, repeatable hiring and onboarding playbook for the NYC team; and the rest of the company asking what you'll automate next.