🚀 Join Coris (YC S22) as a Backend Engineer

Coris is seeking an AI-Native Backend Engineer to spearhead Risk Infrastructure Integrations. We are building the definitive AI-driven operations and risk platform tailored for banks, SaaS companies, and payment processors.

📋 Quick Glance: Role Details

Feature	Detail
Compensation	`$160,000 - $175,000`
Equity	`0.25% - 0.50%`
Location	Palo Alto, CA, US (In-person)
Experience	3+ years
Eligibility	US Citizens or Visa holders only
Core Stack	`Python`, `Django`, `PostgreSQL`, `TypeScript`, `JavaScript`

🧠 What is Coris?

Coris provides an AI-powered ecosystem for financial operations and risk management. Our clients—including Cherry, Clio, and GoFundMe—leverage our platform to accelerate merchant onboarding, maintain constant surveillance, and mitigate fraud without needing to expand their internal teams.

"One customer described us as Cursor + Lovable for risk teams."

We are backed by industry heavyweights like Pathlight, Lux Capital, and Y Combinator. Founded by veterans of the payments space, we are experiencing rapid growth driven by intense customer demand. As a member of our lean team, you will hold significant ownership over the backend architecture.

👥 The Leadership

You will report to and collaborate with:

Vinodh (CEO)
Shyam (CTO)

Both founders bring over two decades of experience in risk and fraud engineering, having led product and operations teams at PayPal, WePay, eBay, and Google.

🚀 The Mission: Why This Role is Critical

The intelligence of Coris depends entirely on the data we ingest. We pull massive volumes of information from providers like TSYS, Fiserv, Adyen, Stripe, and Repay via SFTP feeds, webhooks, and APIs.

The Scale:

Hundreds of millions of monthly events.
Database size $\approx 10^9$ rows in Postgres.

The Challenge: "The Messy Middle"

Data is rarely clean. You will deal with scenarios like:

Timezone Chaos: One processor uses UTC; another uses local time without labeling it.
Schema Drift: A decline code appears in a column different from the official documentation.
Urgency: A client's risk lead reports a discrepancy that requires an immediate resolution.

# Example of the "mess" you'll tame:
# Processor A: {"timestamp": "2023-10-01T12:00:00Z", "status": "declined"}
# Processor B: {"date": "10/01/23 08:00", "err_code": "404", "tz": "EST"}
# Your job: Normalize this into a single, reliable signal.

The Moat: We believe that getting the boring work right every single time is the foundation of an enduring company. Reliable integrations are our competitive advantage.

🛠️ Your Responsibilities

Data Ingestion: Build and maintain pipelines for current and future processors using batch files, webhooks, and APIs.
API & Configuration: Expand the v2 API and create custom signals/configurations, working directly with client ops teams.
The Risk Engine: Develop the DAG engine for scoring transactions; optimize Postgres via partitioning, indexing, and advanced aggregations.
Infrastructure Stability: Manage Celery workers, handle deadlocks, implement circuit breakers, and monitor via Sentry.
AI Integration:
- Utilize coding agents for refactoring and first drafts.
- Implement LLMs for structured extraction, document parsing, and dispute agents.
- Define the company's standards for AI-assisted development.
Frontend Touch: Spend $\approx 10\text{--}20\%$ of your time in Next.js and TypeScript for product features.

🗺️ The First 90 Days

Week 1: Successfully merge and deploy your first PR to production.
Day 30: Independently ship substantial new features.
Day 60: Develop deep expertise in a core system (e.g., the Partner API or the Risk Engine).
Day 90: Become the primary subject matter expert for a major platform component.

🎯 Who You Are

Technical Requirements

Python Mastery: Several years of experience shipping production backends (specifically Django and Postgres). ~~3 years is a hard limit~~ $\rightarrow$ it's a general guide.
Scaling Experience: You've managed systems through growth, dealing with concurrency bugs, large-table schema migrations, and on-call rotations.
SQL Proficiency: You are comfortable reading query plans and optimizing complex joins.
AI-Native Workflow: You use Cursor, Claude Code, or Codex by default. You have built LLM-powered tools that actual people use.

The "AI-Native" Mindset

You know exactly where to trust the agent and where to be skeptical:

Agent-led: Test scaffolding, well-defined refactors, diff-able migrations.
Human-led: $\text{PII/Card Data} \rightarrow \text{Line-by-line review}$ . Schema changes on massive tables or locking logic.

The Cultural Fit

Resilience: You find the "pattern in the mess" of legacy 1995-era file formats and don't burn out.
Customer-Centric: You are happy to jump on a call with a risk team and provide a fast, accurate answer.
Ownership: You want meaningful equity and are comfortable with ambiguity, long hours, and being in the office 5 days a week.

🌟 Nice to Haves

Domain Knowledge: Experience at a PayFac, ISO, or companies like Ramp, Plaid, Adyen, or Stripe.
Specialized Systems: Experience with feature stores, entity-linking, graph systems, or rules engines.
Legacy Tech: Handling PCI-scoped data or fixed-width SFTP batch files.
LLM Production: Experience with evals, tool-use agents, or structured extraction.

⚙️ How We Operate & Interview

Our Philosophy

We prioritize measurable impact and a bias toward action. We ship rapidly and iterate based on real-world feedback. Note: As a high-growth startup, we typically work well beyond a standard 40–50 hour week.

The Pipeline

Pair-Building: Use your own AI tools. We evaluate how you direct the agent and how you verify the output.
Code Judgment: You will review an AI-generated PR against a realistic codebase.

🖼️ Team & Brand

The Founders: Shyam Maddali Vinodh Poyyapakkam