AI Platform Engineer

oneapp; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Remote-friendly role (US)

Flexible time off

Stock options

Health benefits from day one

401(k) with company match

Career growth

Job summary

oneapp is seeking a Platform Engineer embedded in a consumer fintech setting, focusing on AI and automation. You will partner with cross-functional teams to turn AI strategy into production reality, designing reusable agentic systems that automate complex workflows and amplify team output.

The role blends hands-on prototyping, integration work, and enablement, with emphasis on building scalable, secure integrations and playbooks that others can adopt across the company.

Qualifications

• Five+ years shipping prod-grade code that is clean and tested.
• Hands-on AI tooling: LLMs, agent frameworks, AI-assisted tools.
• Experience with REST APIs, SQL data pipelines, cloud (GCP/AWS).
• Product mindset; ability to surface requirements and tradeoffs across teams.
• Create reusable playbooks, architecture docs, and handoff materials.

Responsibilities

• Prototype, deploy, and ship AI agents and automation workflows.
• Lead discovery sessions to surface requirements and translate processes to specs.
• Build secure integrations between SaaS stack and AI services with monitoring and guardrails.
• Coach partners on AI-first mindsets and produce reusable playbooks and docs.

Skills

AI tooling expertise

LangGraph/Claude SDK experience

LLM evaluation methods

REST APIs & cloud (GCP/AWS)

Cross-functional collaboration

Tools

Cursor

Claude Code

Job description

Role overview

A platform engineer role embedded inside a consumer fintech organization, focused on AI and automation. The engineer partners with cross-functional teams to turn AI strategy into production reality, designing and shipping agentic systems that automate complex workflows and amplify team output. The position blends hands-on prototyping, integration work, and enablement, with the expectation that what gets built becomes reusable by the wider organization.

Responsibilities

• Operate as an AI-native engineer using tools like Cursor and Claude Code to rapidly prototype, deploy, and ship production-grade AI agents and automation workflows that solve high-stakes business problems.
• Lead structured discovery sessions with business stakeholders and subject matter experts to surface requirements, assess feasibility, and translate manual processes into clear technical specifications and agentic architectures.
• Build and maintain secure integrations between the core SaaS stack and custom AI services, instrumenting monitoring, guardrails, and evaluation frameworks to ensure workflows are accurate, compliant, and resilient.
• Act as a technical force multiplier by coaching internal partners on AI-first mindsets and producing reusable playbooks, architecture decision records, and handoff documentation so teams can extend and maintain what is built.

Requirements

• Five or more years of professional engineering experience shipping production-grade code that is clean, maintainable, and well tested.
• Hands-on expertise with modern AI tooling: LLM APIs, agent frameworks such as LangGraph or the Claude SDK, AI-assisted developer tools, MCP server development, and LLM evaluation methods including prompt regression testing and human-in-the-loop review.
• Systems integration experience covering REST APIs, SQL data pipelines, and cloud infrastructure on GCP or AWS.
• A product mindset that proactively identifies friction, designs solutions, and presents tradeoffs clearly, paired with the drive to operate across organizational boundaries to get things shipped.

Nice to have

• Familiarity with the broader stack: Node, TypeScript, NestJS, Kubernetes, React Native, or comparable modern engineering tooling.

Benefits and work setup

• Remote-friendly role within the United States
• Flexible time off
• High-growth and mission-driven culture
• Competitive base salary
• Stock options
• Health benefits from day one
• 401(k) plan with company match
• The interview process typically runs through an AI-assisted screen, a talent partner conversation, a technical or hiring manager interview, a team interview, and an executive interview.