AI Engineer - Agentic Systems & AI Infrastructure
New York (Hybrid) - Relocation support available
The Opportunity
A category-defining fintech platform - now valued at ~$10B+ - is building the infrastructure layer for how millions of people interact with housing, payments, and everyday spend.
What started as a rewards product has evolved into a network spanning 4.5M+ homes, enabling users to turn one of their largest expenses into a powerful financial asset.
Now, they’re investing deeply in AI. This role sits at the center of that shift.
You’ll be responsible for building the core AI platform, agent systems, and infrastructure that power how AI is used across the entire company - from engineering workflows to product features to internal operations.
This is not a “plug GPT into a feature” role.
This is: Designing and scaling the systems that make AI actually work in production.
What You’ll Do
- Architect and build a centralized AI platform used across engineering and product teams
- Design and deploy agentic systems, sub-agents, and reusable “skills” for real-world workflows
- Build secure, sandboxed execution environments for autonomous code + task execution
- Integrate AI deeply into the SDLC - CI/CD, testing, debugging, and developer workflows
- Create internal tools (Slack agents, query systems, analytics copilots) that eliminate manual work
- Evaluate and integrate cutting-edge AI tooling into production systems
- Define guardrails, permissions, and safety layers for enterprise-grade AI usage
- Partner closely with engineering leadership to turn AI strategy into shipped system
What They’re Looking For
- Strong backend / infrastructure background - you’ve built and operated complex distributed systems
- Deep hands-on experience with LLMs, agents, or modern AI tooling
- Experience building production systems (not just prototypes)
- Comfort designing systems around:
- security & permissions
- sandboxing & isolation
- reliability & failure handling
- Track record of automating workflows at scale
- Bias toward shipping real systems over experiments
Bonus Points
- Experience with agent frameworks, RAG pipelines, or eval systems
- Built internal platforms or developer tooling
- Worked on AI systems that interface with real business workflows
- Strong product intuition - you care about impact, not just infrastructure
Why This Role
- Massive real-world impact - your systems will power AI across a product used by millions
- Platform-level ownership - you’re building the foundation, not features on top
- High-leverage problems - automation, agents, reliability, and scale
- Strong backing & growth - multi-billion valuation, top-tier investors, rapid expansion
- Real adoption - not experimental AI, but systems embedded into daily workflows
This is a role for engineers who want to:
- Move beyond demos → production AI systems
- Build beyond features → platforms & infrastructure
- Work on AI that’s actually used → at scale, every day
If you’re excited about building agentic systems and real-world LLM infrastructure at scale, we’d love to hear from you.
