Principal Software Developer, Backend

Sketchy

1d•$195,000 - $215,000•Remote

About The Position

Sketchy is building the future of clinical education through storytelling, scalable platforms, and applied AI. As a Principal Software Developer, Backend, you will own the technical direction of our most critical backend systems and AI-enabled services, guiding architecture decisions that balance speed, reliability, and long-term maintainability. You will serve as a technical leader across teams, partnering closely with Product, Design, Data, and Frontend Engineering to turn ambiguous product goals into robust, production-ready systems. This role is ideal for an experienced backend engineer who thrives in high-ownership environments, enjoys mentoring others, and is excited to ship real-world AI systems that directly impact how clinicians learn and practice. Sketchy is hiring remote employees in these select US states: California, Colorado, Florida, Illinois, Massachusetts, Michigan, New Jersey, New York, Pennsylvania, Texas, Utah, and Washington! You’ll thrive here if you: Enjoy owning architecture and technical strategy, not just implementation Turn ambiguity into clear plans, tradeoffs, and execution paths Care deeply about reliability, observability, and operational excellence Believe applied AI should be pragmatic, measurable, safe, and cost-aware Raise the bar for engineering quality through mentorship and example

Requirements

10+ years of experience building and operating production backend systems in consumer and/or B2B SaaS environments, including scaling and distributed systems.
Deep expertise in AWS and cloud-native architectures (EC2, Fargate, Lambda, queues) with Infrastructure as Code (Terraform).
Strong experience with Node.js, TypeScript, and modern backend frameworks (NestJS or equivalent).
Experience with Redis, Postgres, SQL, and data-intensive backend systems.
Proven ability to design scalable architectures and lead complex technical decisions across APIs, data models, async workflows, caching, and migrations.
Strong experience with Docker, CI/CD pipelines, and production deployment patterns.
Expertise in observability, reliability, and cost optimization (metrics, logging, tracing; e.g., Datadog).
Excellent communication skills and a strong record of ownership and delivery in fast-moving startup environments.
Hands-on experience shipping AI-enabled features into production, including LLM-backed workflows, retrieval patterns (RAG, embeddings, vector databases), evaluation and guardrails, and monitoring for quality, latency, cost, and model drift.

Nice To Haves

Experience building internal platforms or developer tooling
background in edtech or learning analytics
familiarity with modern privacy and security best practices (PII handling, least privilege, secure-by-default).

Responsibilities

Own architecture and technical direction for major backend systems and initiatives, balancing product velocity with reliability, scalability, and long-term maintainability.
Lead cross-functional delivery with Product Managers and Designers by translating ambiguous problems into clear technical plans, milestones, and measurable outcomes.
Design, build, and operate applied AI systems in production, including: LLM-backed workflows and services Retrieval patterns (RAG), embeddings, and vector stores Evaluation frameworks, guardrails, and quality measurement Monitoring for latency, cost, failures, and model drift
Establish and uphold engineering best practices across the backend organization, including code quality, testing strategy, documentation, operational readiness, and incident response.
Act as a force multiplier through technical mentorship, pairing, architecture reviews, and raising standards across the engineering team.
Drive operational excellence by improving observability, performance tuning, cost efficiency, system reliability, and on-call outcomes.
Participate in an on-call rotation to support production systems and lead investigations when issues occur.
Break down complex product requirements into well-scoped workstreams that enable predictable execution and high-quality delivery.