Hiring: Founding Engineer, June Company: SecureVision Location: Tysons Corner, VA Job Posted Time: 2026-09-02 18:06:15 Target Skills & Keywords : App Engine, Clean Architecture, Compliance, FastAPI, GCP, IAM, LLM, Make, OAuth, PATs, PostgreSQL, Python, Redis, SQL, jQuery About the job Required Skills: •SecureVision Embedded RPO is posting this job for June. June is hiring a 10x •Founding Engineer •technical delivery and architecture •for our AI-assisted hiring platform. You’ll work •hands-on in the backend •, partner closely with product, and be the person who •clears urgent customer issues •in messy real-world environments while •raising the bar on reliability, security, and design •as we scale. •June is at an early and critical stage, onboarding •several enterprise customers, •and we will start fundraising for our Seed round in the next few months. We are looking for a Founding Engineer with a •strong entrepreneurial desire •to make an impact at the ground level and build a category defining product. Compensation: •A strong equity position is negotiable. •What You’ll Do •Architecture & technical leadership: Define and evolve the system architecture (services, data model, integrations, async work, observability). Make pragmatic tradeoffs between speed and durability for an early-stage company. •Customer-critical firefighting: Diagnose and fix production and integration issues (ATS sync, telephony/messaging, AI pipelines, auth, cloud networking). Turn incidents into lasting fixes (runbooks, tests, monitoring). •Backend ownership: Ship and refactor core APIs and workflows in Python/FastAPI, Postgres, Redis, background jobs/tasks, with strong attention to correctness, performance, and maintainability. •Cloud & platform engineering: Operate comfortably in GCP (e.g., App Engine, Cloud SQL, IAM, secrets, queues). Improve deployment confidence, cost awareness, and operational hygiene. •Security & compliance mindset: Apply sound defaults for secrets handling, access control, data handling, and vendor integrations; partner on customer security reviews when needed. •Mentorship: Raise the bar for the whole team—reviews, patterns, and lightweight documentation that speed everyone up. •Applied AI product engineering: Design and iterate on LLM-powered workflows (prompting, tooling, evaluation harnesses, guardrails, cost/latency tradeoffs) so AI features are reliable in production, not just impressive in demos. •AI Ops in production: Own monitoring, regression detection, and safety for AI paths—structured logging around model calls, failure modes, retries/timeouts, versioning of prompts/agents, and measurable quality over time (evals, sampling, human-in-the-loop where appropriate). Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!