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Location
San Francisco, CA
Salary
$150,000 - $275,000
Type
Full-Time
About Kastle
Kastle is the AI operating system for consumer lending, starting with mortgage. They build AI voice and SMS agents that mortgage lenders deploy across contact centers, collections, and compliance operations. The product handles payment collection, escrow questions, new loan qualification, and delinquent-borrower engagement — automating call and text workflows that historically required teams of humans working long hours. Kastle scores each AI call against the lender's own quality framework to guarantee regulatory compliance (FDCPA, RESPA, TILA).
Traction:
- Over $1 billion in payments processed to date
- ~$6M+ in revenue generated in 2026
- Growing from 10 people to 30 by end of 2026
Backed by Y Combinator (S24 batch), Commerce Ventures, and executives from Snapdocs, Google, and WePay.
Why this matters: mortgage servicers are structurally short-staffed on inbound call volume that spikes with delinquency cycles. Borrowers wait in queues to make payments. Compliance is unforgiving. Kastle's bet is that AI voice + SMS agents — with airtight regulatory grounding — can cut cost-to-service by 80% while giving borrowers 24/7 access and giving lenders auditable, always-compliant interactions.
Why Kastle
Tweets, press, and people that show why this team is worth your time.
Link
Kastle joins Y Combinator's Summer 2024 batch
Kastle was selected for Y Combinator's prestigious Summer 2024 cohort, highlighting its potential in the AI-driven mortgage servicing space.
Link
Nitish Poddar, Co-Founder and CTO of Kastle, joins Forbes Business Council
Nitish Poddar's inclusion in the Forbes Business Council highlights his leadership and expertise in AI and mortgage servicing.
About This Role
Kastle is hiring Members of Technical Staff — internally referred to as founding engineers. The mandate is to architect and own the core systems that power Kastle's real-time AI voice and compliance workflows for top-10 US mortgage lenders. Someone who's a little bit more infra / backend.
The archetype is the engineer who comes in, has an opinion on how the product should actually be built, and starts rebuilding it.
What You'll Own
- Architect and own core systems that power real-time AI voice and compliance workflows
- Push performance boundaries — sub-700ms latency via event-driven architecture and parallel processing
- Deploy, operate, scale resilient systems using Kubernetes and distributed sub-systems
- Build a self-improving AI system that improves with every customer interaction and human feedback
- Ship fast, ship right — whiteboard design to live production in bank environments
- Set engineering culture and best practices — code reviews, docs, architecture decisions
Requirements
- 3+ years professional engineering experience
- Strong Python fundamentals
- Strong backend + infrastructure depth — has personally architected production backends, not just shipped within someone else's stack
- Deep understanding of distributed systems, reliability, fault tolerance
- Excellent database design and performance optimization
- Strong opinions on architecture with bias to defensibly rebuild what's wrong
- Bias for ownership — figures things out in messy, high-velocity environments
- SF-based or willing to relocate immediately — 5 days/week
- Cracked with AI tooling — Claude / Cursor / Codex daily
- Genuine interest in mortgage / lending space — documented failure mode
- Visa: H-1B transfer OK, TN OK (no OPT; O-1 too slow)
Profile Tier 1 — Distributed Systems / Low-Latency Backend at High-Bar Companies
- AWS distributed systems / low-latency teams
- Palantir Foundry infrastructure / platform teams
- Databricks, Snowflake compute layer / infra
- CockroachDB, MongoDB, Confluent, Vespa, Pinecone, Weaviate, Elastic, Clickhouse, Materialize, Neon, PlanetScale, Convex, Supabase infra
- Verkada — direct culture and technical match
Tier 2 — AI Infrastructure / Voice Infrastructure Engineers
- Anthropic Applied / Production Infra, OpenAI Solutions / Production Infra, Together AI, Fireworks AI, Modal, Replicate, Anyscale, Cohere infra
- Voice infra: Deepgram, Cartesia, ElevenLabs infra, Retell, Vapi, Bland, Air.ai, PolyAI, HappyRobot
- Twilio infra, Vonage infra
- Real-time / sub-second production systems
Tier 3 — Ex-YC Founding Engineers with Backend Depth
- YC founders and founding engineers of companies with real backend architecture. Especially data-intensive or infra-heavy YC products
Tier 4 — Impressive Fast-Moving Startups with Real Infra
- Perplexity, Cursor, Vercel, Modal, Replicate infra teams
- Mercor, Weap, Sierra, Decagon, Glean, Cresta infra
Tier 5 — Compliance-Heavy Vertical AI Infrastructure
- Harvey, Eve, Spellbook — legal AI infrastructure
- Blend, Ocrolus, Truework, Snapdocs, Rocket Companies — mortgage / lending infra
Tier 6 — Big Tech Infrastructure with Zero-to-One Signal
Strong Bonuses
- Kubernetes production experience
- Event-driven architecture, parallel processing
- Sub-second latency systems — voice AI, HFT, ad-serving, real-time bidding, real-time recommendation
- AWS distributed systems
- Verkada alumni
- Compliance-heavy production systems — FDCPA / RESPA / TILA / HIPAA / SOC 2 / PCI
- Voice / telephony / real-time media infrastructure
Location and Visa
- H-1B transfer OK, TN OK, OPT is a hard no, O-1 acceptable
Job Details
Experience
3-8 years
Salary
$150,000 - $275,000
Equity
Yes
Visa Sponsorship
Yes
Employment Type
Full-Time
Benefits & Perks
401(k) Match
Lunch And Dinner Covered
Standard Medical / Dental / Vision
Relocation Support
Green Flags
AWS distributed systems / low-latency engineer
Palantir Foundry infrastructure
Verkada alumni — direct culture and technical match
Red Flags
Under 3 years without AWS distributed-systems exception
Pure ML researcher
Product engineer in disguise as backend
Required Candidate Q&A
Question 1
Are you SF-based or willing to relocate immediately, and comfortable being in-person 5 days/week?
Question 2
What's your US work authorization status?
Candidate scorecard
· 13 criteria3+ years professional engineering experience
Strong Python
Deep distributed systems, reliability, fault tolerance understanding