About The Position

This is a contract-to-hire, player-coach role at a high-growth coaching and personal development company. The engineer will lead a small development team while personally contributing production code, making pragmatic architecture decisions, and owning complex product and platform work in partnership with Product and the existing platform architect. The initial contractor period is three months, with an opportunity to transition to a full-time W2 position with benefits based on performance. A core requirement is experience building proprietary AI capabilities for an AI SaaS product from the ground up. The role involves owning the AI application layer and production systems, including retrieval and RAG pipelines, embeddings and vector search, persistent memory and member context, stateful workflows, tool use, orchestration, guardrails, and AI-driven personalization. Using foundation models or third-party model APIs is compatible with the role; the key requirement is ownership of the underlying AI product architecture and functionality. The engineer will assess and improve the existing production codebase for security, scalability, performance, architecture, data protection, and reliability risks, and will take increasing ownership of the platform’s technical health. Responsibilities span the full stack, with a strong backend focus and hands-on Vue.js frontend work. The role also covers end-to-end feature ownership, relational data design and performance, integrations, testing, deployment, monitoring, production support, and technical coordination with outside engineering partners. The position is not available to candidates in California, New York, New Jersey, or Pennsylvania, and requires availability for at least five to six hours overlapping an 8–5 or 9–6 MST schedule.

Requirements

  • 8 to 12+ years of software engineering experience.
  • Strong production experience with Vue.js.
  • Deep hands-on experience with relational database design.
  • Strong experience owning significant portions of a production platform across backend architecture, databases, APIs and integrations, infrastructure, deployment, monitoring, troubleshooting, and production support.
  • Proven experience developing an AI-native SaaS product or substantial proprietary AI product capability, from initial architecture through production launch and ongoing operation.
  • Experience assessing production applications for security, scalability, reliability, and performance risks, including identifying vulnerabilities, protecting sensitive customer data, diagnosing bottlenecks, and implementing pragmatic improvements.
  • Demonstrated technical leadership of small development teams, including hands-on mentorship, architecture reviews, work planning, coordination, and shipping results while personally contributing code.
  • Experience reviewing and validating engineers’ or external development partners’ work, including architecture decisions, code quality, testing, security, scalability, and production readiness.
  • Ability to quickly understand and contribute within an existing codebase and technical direction, identifying material risks and making pragmatic improvements rather than defaulting to unnecessary rewrites or redesigns.
  • Experience owning production readiness, including monitoring, incident troubleshooting, release processes, technical QA, and resolving critical production issues.
  • Proven experience using AI coding agents on a production codebase to improve productivity without replacing sound engineering judgment.
  • Highly organized and self-sufficient, able to operate independently and make sound technical decisions in a fast-paced environment.
  • Comfort working in a startup environment, adapting to changing priorities, and taking increasing technical ownership as the company scales.
  • Availability for at least five to six hours overlapping an 8–5 or 9–6 MST schedule.
  • The position is not available in California, New York, New Jersey, or Pennsylvania.

Nice To Haves

  • PostgreSQL experience is preferred.
  • Experience with Nuxt is a plus.
  • Experience with Prisma is a plus.

Responsibilities

  • Lead a small engineering team by setting technical direction within agreed product priorities, mentoring developers, delegating work, conducting code and design reviews, coordinating contractors, removing blockers, and maintaining accountability for quality and delivery.
  • Design and implement proprietary AI product capabilities, including retrieval and RAG pipelines, embeddings and vector search, persistent memory and member context, stateful workflows, tool use, orchestration, guardrails, and AI-driven personalization.
  • Assess the production codebase for security vulnerabilities, scalability and performance bottlenecks, architecture risks, data protection concerns, and reliability issues; prioritize and implement pragmatic improvements for a safe, stable public launch.
  • Take increasing ownership of the platform’s technical health and architecture, including stability, security, scalability, reliability, and continued evolution.
  • Own features end to end, from data modeling and architecture through implementation, testing, deployment, monitoring, and production support.
  • Work across the full stack with a strong backend focus and contribute hands-on to Vue.js frontend development and customer experience.
  • Act as the internal technical counterpart to outside engineering partners by reviewing architecture and code, challenging technical decisions when appropriate, validating deliverables, and ensuring product, security, scalability, and production requirements are met.
  • Partner with the existing platform engineer on technical knowledge transfer covering architecture, codebase, environments, infrastructure, accounts, deployment processes, documentation, and operational procedures.
  • Design, automate, and execute functional, regression, load, and smoke testing.
  • Design and evolve relational data models, PostgreSQL schemas, queries, indexes, migrations, and Prisma models.
  • Work across integrations including Stripe Connect, LiveKit, Twilio, Zoom, Anthropic, and pgvector.
  • Use AI coding agents to accelerate development while maintaining standards for correctness, reliability, security, and maintainability.
  • Own production readiness, including monitoring, incident troubleshooting, release processes, technical QA, and resolving critical production issues.

Benefits

  • Multiple medical insurance options with an employer contribution toward medical insurance premiums (after transition to direct hire).
  • Dental and vision insurance options (after transition to direct hire).
  • Supplemental life insurance (after transition to direct hire).
  • Voluntary short-term and long-term disability insurance (after transition to direct hire).
  • 15 days of paid time off annually (after transition to direct hire).
  • 7 paid company holidays (after transition to direct hire).
  • Access to company-certified coaches and personal development opportunities (after transition to direct hire).
  • Opportunities to attend company live events (after transition to direct hire).
  • Travel and leisure membership benefits (after transition to direct hire).
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