- Map out data flows, systems, and constraints directly with customers early in engagements
- Rapidly deliver lean technical prototypes or “pilot skeletons” within days (not weeks) to validate assumptions and reduce risk.
- Ask critical questions: "What data do they actually have vs what they say they have?" to drive action.
- Develop robust connectors to core campus systems (APIs, batch exports, SFTP, legacy or undocumented endpoints).
- Normalize, clean, deduplicate, and reconcile schemas; rigorously handle edge cases (misformatted data, missing keys, duplicates).
- Implement reliable write-backs (idempotent writes, partial updates, rollbacks, conflict detection).
- Automate resilience: retries, backoff strategies, rate-limit protection, error logging, and alerting.
- Create deployment playbooks, scripts, and infrastructure-as-code templates for rapid, repeatable pilot deployments.
- Develop monitoring, observability, and dashboards to track pipeline health, error rates, latency, and data drift.
- Document runbooks, rollback plans, and detailed incident-handling procedures.
- Instrument key metrics such as records processed, failure rates, time saved, and errors prevented.
- Provide clear dashboards and summaries to demonstrate measurable value to customers and internal teams.
- Maintain accountability, own the resolution if pilots fail to meet defined targets.
- Engage directly with customer engineers, data teams, operations staff, and executives to facilitate onboarding and handle escalations.
- Guide customer teams through schema mapping, data permissions, and compliance requirements.
- Act as escalation owner during pilot phases; swiftly investigate and resolve alerts and issues.
- Capture and communicate field constraints, corner cases, and failure modes.
- Convert these learnings into prioritized product enhancements, reusable libraries, and product abstractions.
- 1–5 years in software engineering, particularly backend or data integration roles.
- Strong Python skills, solid SQL/data modeling experience, and comfort with basic frontend work (React/TypeScript).
- Practical integration experience (REST APIs, CSV/SFTP, OAuth/SAML, legacy endpoints).
- Confidence in debugging across multiple layers: logs, databases, networks.
- Clear, warm communication—comfortable presenting to technical and non-technical audiences.
- A mindset for automation and repeatability.
- Basic awareness of security/privacy best practices (FERPA/GDPR).
- In-person commitment: We are together in the office 5–6 days a week. Building at this stage requires full presence and focus.
- Speed and impact: We measure progress by the day, not the quarter. Your work ships fast and affects students immediately.
- Mission clarity: Every line of code and every late night ties back to one purpose—helping students stay enrolled and helping colleges survive.
- Ownership from day one: You will make critical decisions, drive outcomes, and build Risely alongside the founders.
- Deep, meaningful work: You will tackle data complexity, privacy laws, and legacy integrations. The problems are tough, but solving them matters.
What We Do
Risely’s AI agents automate administrative and manual tasks across college campuses. Our AI Advisor identifies and flags at-risk students, crafts personalized outreach, and creates tailored success plans - all in natural language. Risely integrates directly into existing university systems (SIS, LMS, CRM) and learns each institution’s unique workflows. This dramatically reduces the $735 billion universities spend annually on administrative labor, expands staff capacity without increasing headcount, and improves the student experience. University workflows require nuanced, autonomous judgment, exactly what agentic AI was designed to solve. Our team uniquely combines deep expertise in higher education, enterprise-scale AI, and regulated enterprise sales. We're grateful to be backed by Y Combinator.







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