Principal AI Engineer

About Synply
Synply is building the software and payments platform for the syndicated lending market an industry still run on spreadsheets, PDFs, and email. We’re an early-stage fintech on a mission to modernize how banks and lenders originate, manage, and settle syndicated loans.
About the Role
We’re hiring our first dedicated AI engineer. This is a founding, hands-on role for someone who ships fast and goes deep when it matters not a research role, and not a management role.
You’ll sit next to product and build AI-powered features into our production platform. You’ll also reshape how we build: evaluation harnesses, spec-driven development, and agentic coding workflows the whole engineering team adopts.
We’re looking for someone fast with modern AI tooling and rigorous underneath it. You should be able to stand up a working prototype in a day with coding agents and also read a thread dump, reason about a consumer group rebalance, or fix a query plan without one. In syndicated lending the failure modes are quiet: a silently wrong extraction on an amendment propagates into positions and settlement. Catching that class of problem is an engineering judgment question before it’s an AI question.
What You’ll Do
Build customer-facing AI features end to end document understanding, data extraction, workflow
automation across the loan lifecycle from POC through production, in our stack
Prototype quickly with AI coding tools, then own the production version: architecture, tests, observability,
security, cost
Design and own evaluation frameworks golden datasets, regression suites, accuracy/cost/latency
budgets so we can ship against financial data with a defensible quality bar
Establish spec-driven development: specs as the source of truth for engineers and coding agents alike, with acceptance criteria that survive review
Build internal AI tooling that makes engineering, operations, and go-to-market measurably faster
Select models, frameworks, and vendors per use case, and rip out the wrong choice early
Work directly with product to find where AI creates real leverage and push back where it doesn’t
Set the technical bar for AI work as the team grows: mentorship now, formal leadership later if you want it
What We’re Looking For
Engineering foundation
8+ years of production software engineering. You’ve designed systems others built on, debugged failures under pressure, and lived with the consequences of your own architecture.
Real command of the fundamentals: concurrency, distributed systems failure modes, data modeling, transaction semantics, API and schema design, testing strategy, security. You can explain why a design holds, not just that it works.
You’ve operated what you built on-call, incident response, the postmortem afterward.
Comfortable owning a strongly-typed JVM backend (Java/Spring) plus the data layer (Postgres, Kafka) and enough Angular to ship the UI yourself.
Modern AI leverage
You get serious throughput out of coding agents and AI-assisted workflows, and you know precisely where to stop trusting them.
You’ve taken agent-generated work and hardened it to production standard tests, observability, security review, behavior under load.
Recent hands-on LLM engineering in a shipped product: prompt and context design, retrieval, tool use, evaluation, cost and latency tuning.
Strong opinions on maintaining quality in non-deterministic systems.
Domain and environment
B2B banking, capital markets, or financial infrastructure. You understand the compliance, audit, and accuracy expectations that come with financial data.
Startup experience: ambiguity, no playbook, shipping under real constraints.
Bonus
Syndicated lending, loan servicing, or agency operations
Other document-heavy or extraction-heavy domains (legal tech, insurance)
Prior tech lead or mentorship experience
Our Stack
AWS, Java and Spring, Angular, Kafka, Postgres. We care more about depth than a checklist match.
How We Interview
A live design and debugging session without AI assistance, plus a working session where you use your normal tooling. We want to see both.
Why Synply
Ground-floor opportunity to define what applied AI means for an entire category of financial infrastructure
Direct exposure to customers, leadership, and company strategy
High ownership, fast decision-making, and a path to leading a team as we grow

Work arrangement
No