[All remote jobs](https://jobicy.com/jobs.md)[![Neuroscale AI logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2026/11/42e007548885-221.webp)](https://jobicy.com/company/neuroscale-ai.md)[Neuroscale AI](https://jobicy.com/company/neuroscale-ai.md) # Founding Member of Technical Staff AI Summary Neuroscale AI is hiring a founding technical staff member to build AI-powered recruiting and federal workflow products. The engineer will work directly with founders to design and ship end-to-end features, with a strong emphasis on LLM-based agents, search quality, candidate conversations, and regulated multi-tenant deployments. The stack includes Next.js, React, Node.js, Python FastAPI, OpenSearch, Temporal, AWS, and multiple inference providers. This is an early-stage, high-ownership onsite role in Northern Virginia for a builder with strong product judgment and startup execution ability.[Apply for this job](#job-application)[View company](https://jobicy.com/company/neuroscale-ai.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUndisclosedDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceSeniorPublished12 Nov 2026Apply before12 Dec 2026Listing views36Application actions3Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. About Neuroscale Neuroscale is on a mission to fill the world’s most important roles. Recruiting is a zero-sum game. The best people get hired once, and the teams that move fastest win. We build Arbi, an AI recruiting platform that combines autonomous agents with elite recruiters so world-class companies and federal agencies can hire well and grow fast. Arbi searches 800M+ profiles, runs outreach, and interviews candidates at scale. Through every search, placement, and interaction on our platform, we capture proprietary hiring data that no one else has at scale, and that data powers the agentic systems we are building to make hiring faster, smarter, and more precise. We believe AI will create more jobs, not less. As companies move faster with fewer constraints, they will hire more ambitiously and for roles that did not exist before, making the hiring layer more critical than ever. We hold a USAF SBIR Direct-to-Phase-II contract, sell into federal through Carahsoft, and work with enterprise, federal, and regulated organizations that most AI startups cannot touch. Our second product, Athena, extends the same agent infrastructure into federal agency workflows. We are a small, founder-led team and this is one of the first engineering seats. About the Role You will work directly with the founders on the hardest technical questions in the product: * How do we understand the nuance in a hiring requirement well enough to find the person a filter & criteria search never would? * How do we interview candidates at scale and turn those conversations into a data edge no public profile can give you? * How do agents decide who to reach out to, what to say, and when to hand off to a human? * How do we make a recruiter say “wow” in the first five minutes? You will design, build, and ship features end to end, most of them built on LLMs. Recent work includes agent execution infrastructure, feedback loops that improve search quality from recruiter behavior, and multi-tenant deployment for regulated customers. Our stack: Next.js + React, Node.js, Python FastAPI, OpenSearch (Elasticsearch), Temporal, and a range of inference providers and models. About You * You have built something from scratch. A startup, a product, a system people depend on. * You ship. We care more about what you have built than where you have worked. * You are high agency. You find the highest-leverage problem, decide it is yours, and attack it. * You have shown excellence somewhere: work, school, open source, a side project that took off. * You take asymmetric bets. Joining a founding team is one of them. * You have real experience with the core of our stack: Next.js, Node.js, AWS, and search or data infrastructure. * Experience with LLM products, voice or conversational AI, or search at scale is a plus, not a filter. * Based in or willing to relocate to Northern Virginia. We build in person. Why Founding * Direct ownership of core systems from day one. Your decisions become the architecture. * Meaningful founding equity. You should share in what you build. * Work on problems with real stakes: federal hiring, regulated industries, roles that matter. * A front-row seat to going from early traction to category leader. Compensation and Benefits * Competitve salary plus meaningful founding equity. * Comprehensive health, dental, and vision coverage. * Meals provided in office. * Relocation support for the right candidate. [Neuroscale AI](https://jobicy.com/company/neuroscale-ai.md) is an equal opportunity employer. Show more [Apply now >](https://jobicy.com/jobs/161562-founding-member-of-technical-staff.md) > Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a founding engineering position involving ambiguous technical problems, end-to-end ownership, and high-stakes systems for regulated customers. Success requires both deep hands-on engineering and rapid product decision-making with minimal structure. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$210,000US market range (per year)$180k–$250k0$275k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer does not disclose a numerical salary range, only stating that compensation includes a competitive salary and founding equity. The annual cadence is inferred from the full-time US founding-engineer context. Estimated US market base pay for a founding-level technical staff member with this stack and responsibility is approximately USD 180,000 to USD 250,000 per year, excluding equity. ## Core skills Skills and capabilities most closely associated with this opportunity. [Next.js](https://jobicy.com/jobs?search_keywords=Next.js.md)[React](https://jobicy.com/jobs?search_keywords=React.md)[Node.js](https://jobicy.com/jobs?search_keywords=Node.js.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[FastAPI](https://jobicy.com/jobs?search_keywords=FastAPI.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[OpenSearch](https://jobicy.com/jobs?search_keywords=OpenSearch.md)[Elasticsearch](https://jobicy.com/jobs?search_keywords=Elasticsearch.md)[Temporal](https://jobicy.com/jobs?search_keywords=Temporal.md)[LLM applications](https://jobicy.com/jobs?search_keywords=LLM%20applications.md)[AI agents](https://jobicy.com/jobs?search_keywords=AI%20agents.md)[Search infrastructure](https://jobicy.com/jobs?search_keywords=Search%20infrastructure.md)[Multi-tenant architecture](https://jobicy.com/jobs?search_keywords=Multi-tenant%20architecture.md)[Cloud deployment](https://jobicy.com/jobs?search_keywords=Cloud%20deployment.md)[Product engineering](https://jobicy.com/jobs?search_keywords=Product%20engineering.md) Sample interview questionsDescribe a product or system you built from scratch and the most important technical decisions you made.I would explain the customer problem, the architecture I selected, key trade-offs, how I shipped an initial version quickly, and how I improved reliability and scale using production feedback and measurable outcomes. How would you design an agent workflow that identifies candidates, drafts outreach, and hands off qualified conversations to recruiters? I would separate the workflow into retrieval, ranking, policy-constrained generation, execution, and human-review stages. Each stage would have observable inputs and outputs, evaluation metrics, audit logs, and feedback loops so recruiter actions can improve ranking and messaging over time. What approach would you take to improve relevance in a large-scale candidate search system? I would combine structured filters with semantic retrieval and learned ranking signals. I would instrument recruiter behavior, track search-to-contact and contact-to-placement outcomes, run offline relevance evaluations, and use controlled experiments to validate improvements. How have you handled ambiguity and competing priorities in an early-stage environment? I start by clarifying the business objective, defining the smallest valuable outcome, and identifying technical risks. I communicate trade-offs early, deliver an incremental solution, and use user feedback and operational data to decide what to deepen or change. How would you design a multi-tenant platform for regulated customers? I would establish strong tenant isolation across identity, data access, storage, and observability. The design would include least-privilege authorization, encryption, audit trails, environment controls, deployment automation, and clear operational boundaries that support compliance requirements. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. 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