Founding Platform Eng Lead
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Before you apply
Salary$150k – $215k
LocationSan Francisco Bay Area , San Francisco, United States
Work modeon-site
Typefull-time
SeniorityLead
Experience3–8 yrs
EquityIncluded
Company size11–50 people
PostedMay 11, 2026 · 5mo ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Systems thinker
Technically strategic
Abstraction taste
Investment judgment
Master of many threads
AI-native
3-8 years of production engineering
Backend: Python and TypeScript in production
Backend: Postgres, schema design at scale, query performance under real load
Infrastructure: AWS or GCP, Kubernetes or equivalent, CDK preferred
Data engineering: Large-scale data pipelines, ETL or ELT, real-time sync, schema evolution
Data engineering: Experience integrating against third-party source systems (Salesforce, Workday, Banner, Snowflake, or comparable)
Multi-tenant patterns: Tenant isolation, encryption at rest and in transit, RBAC, audit trails
LLMs and agents: Built with leading foundation model APIs
LLMs and agents: Designed evaluation pipelines for non-deterministic systems
LLMs and agents: Shipped agent products to production
Skills
Python
TypeScript
PostgreSQL
AWS
GCP
Kubernetes
CDK
Salesforce
Workday
Banner
Snowflake
Claude Code
Founding Platform Engineering Lead
About the role
Location: Downtown San Francisco · in-person 5 days a week · reports directly to the CEO
Comp: $150-215K total cash (incl. variable) plus founding-level equity
About the company
Risely is building the agentic operating system for universities. We’re live at some of the largest universities in the country and growing fast.
We’re hiring our Founding Platform Lead. This is a player-coach role at the foundation of the company. You’ll own and build the core platform that delivers end-to-end deployments to large universities at record speeds with excellent quality.
What you’ll own
•
The platform that delivers in 4 weeks. Most companies in our space take 12 months to deliver an implementation. The platform you own compresses three things in parallel: the data layer against the customer’s source systems, the agent configuration against their workflows, and the security and sync infrastructure each customer inherits. Today, a complex deployment can take us 10-12 weeks to get done, down from 12 months. Your job is to take it lower, and keep it there as the customer base grows from 10 to 40 to 400.
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The deployment automation. A pipeline of agents that does the work an engineering team would otherwise do manually for every customer. You own how they’re designed, how they’re evaluated, where humans stay in the loop, and how the next leap in deployment speed comes out of the same team.
•
The security platform. Compliance, RBAC, encryption, audit trails, agent guardrails. You design the primitives once and own the security posture as we scale into the largest education systems in the country.
•
The connector and data engineering strategy. Every customer brings a new source system, a new schema, a new data contract. You set the strategy for how Risely meets that complexity, and build the framework every new connector inherits.
Who you are
•
Systems thinker. You design at the level of the whole platform. You see dependencies before you change anything.
•
Technically strategic. You solve hard business problems with platforms and systems. When a customer brings a new compliance requirement, a new data shape, or a new integration target, you design the abstraction that makes the next ten customers with the same problem ship on the platform you already built.
•
Abstraction taste. You know which patterns deserve to become primitives. You know when to invest in the platform layer and when to leave a customer feature as bespoke code.
•
Investment judgment. You know when to stop adding surface area and reinforce the platform underneath. You’ve made that call and you’ve been right.
•
Master of many threads. You run several concurrent workstreams without dropping the ball on any of them and you’re able to keep the team posted on all threads at any time
•
AI-native. You orchestrate Claude Code agents to multiply yourself. You ship more in a week as a one-person team than most companies ship in a month with five. As we grow into a small squad, you teach the same way of working.
Experience
3-8 years of production engineering. You’ve built and operated systems at the level of the things we’re hiring you to lead:
•
Backend. Python and TypeScript in production. Postgres, schema design at scale, query performance under real load.
•
Infrastructure. AWS or GCP, Kubernetes or equivalent, CDK preferred. You understand how to make the calls on cost, latency, blast radius, and failure modes.
•
Data engineering. Large-scale data pipelines, ETL or ELT, real-time sync, schema evolution. You’ve integrated against third-party source systems (Salesforce, Workday, Banner, Snowflake, or comparable) and lived with the edge cases.
•
Multi-tenant patterns. Tenant isolation, encryption at rest and in transit, RBAC, audit trails. You have a position on shared versus isolated infrastructure and per-customer cost accounting.
•
LLMs and agents. You’ve built with leading foundation model APis, designed evaluation pipelines for non-deterministic systems, and shipped agent products to production. You have a working point of view on what an agent should own and where humans need to stay in the loop.
We weigh the work itself: what you’ve shipped, what you’ve owned, what broke and what you fixed.
Hunger and grit matter. You’re the kind of engineer who goes out of their way to think about how a problem could be solved differently, and then ships the answer the next morning.
You’re joining the founding team. The work, the pressure, and the equity are all founder-grade.
How to apply
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