Qureos Mentor

David Joseph & Company

<div><p><b>San Francisco, CA &middot; On-site &middot; Full-time</b><br>
<b>Compensation:</b> $130,000&ndash;$150,000 base (up to $300K total cash comp) + equity</p><h3 class="jobSectionHeader"><b>
About the Company</b></h3><p>
A fast-growing, venture-backed AI company building the training data and evaluation infrastructure that leading frontier AI labs use to improve their models &mdash; designing high-signal datasets and running rigorous evaluations that go beyond static benchmarks. One of the fastest-growing companies in its cohort.</p><p>
Founded 2025 &middot; 11&ndash;50 people &middot; Industry: AI training data &amp; model evaluation infrastructure</p><h3 class="jobSectionHeader"><b>
The Role</b></h3><p>
A founding-level role at the intersection of technical execution and strategic leadership. You'll own high-impact initiatives end-to-end &mdash; from requirements through delivery &mdash; managing teams of engineers, data scientists, and ML specialists while shipping production code yourself, and interfacing directly with research teams at leading AI labs.</p><p><b>
What you'll be doing</b></p><ul><li>
Own end-to-end technical initiatives: scoping requirements, building solutions, managing experts through delivery, and shipping code yourself when it unblocks the team.</li><li>
Design and build technical infrastructure and tooling for dataset generation, quality control, and delivery pipelines across multiple concurrent lab contracts.</li><li>
Manage and mentor teams of software engineers, data scientists, and ML specialists; set technical direction and hold the bar for execution velocity.</li><li>
Interface directly with research teams at leading AI labs to translate their needs into technical specs and ensure delivery meets their standards.</li><li>
Debug production issues live under pressure; rapidly context-switch between hands-on engineering, team leadership, and strategic problem-solving.</li><li>
Support the founding team on the highest-impact work &mdash; internal tooling, major contracts, and hiring.</li></ul><p><b>
Tech stack:</b> Python; data pipelines, APIs, ML/AI tooling</p><h3 class="jobSectionHeader"><b>
Requirements</b></h3><ul><li>
CS degree, engineering experience, or equivalent demonstrated ability to ship technical projects</li><li>
Manage teams of technical experts across software engineering, data science, and machine learning</li><li>
Build technical infrastructure and tooling for dataset generation, quality control, and delivery pipelines</li><li>
Drive technical and operational initiatives end-to-end: scoping requirements, building solutions, and managing technical experts</li><li>
Interface directly with engineering and research teams at leading AI labs</li><li>
Support founding team on high-priority technical projects and operational initiatives</li><li>
Proficiency in Python and production-quality code</li><li>
Experience with data pipelines, APIs, or ML/AI tooling</li><li>
Strong leadership experience and communication skills</li><li>
Ability to context-switch rapidly between technical and strategic work</li><li>
Intense work ethic, agency, and drive</li><li>
Competitive nature and track record of exceptional achievement</li><li>
Undergraduate degree from the U.S., Canada, or the U.K.</li></ul><h3 class="jobSectionHeader"><b>
Green Flags</b></h3><ul><li>
Background in software engineering, ML engineering, AI research, or computer science</li><li>
Experience at top tech company (FAANG, frontier AI lab) or quantitative trading firm</li><li>
Prior startup experience or founding experience</li><li>
Willingness to work long hours and weekends when projects demand it</li></ul><h3 class="jobSectionHeader"><b>
Red Flags</b></h3><ul><li>
Worked cushy tech jobs (FAANG PM, etc.) and may not be used to intense work environments.</li><li>
Struggles with ambiguity or lacks examples of owning large, complex projects.</li><li>
Only interested in remote work &mdash; role is strictly in-person.</li><li>
Can't articulate why they want to pivot into AI ops or join a startup now.</li><li>
No experience managing teams or unclear on motivating people toward execution.</li></ul><h3 class="jobSectionHeader"><b>
Why Join</b></h3><ul><li>
Direct access to the founding team on their highest-priority problems</li><li>
Exposure to leading frontier AI labs; work that powers major contracts</li><li>
Up to $300K total cash comp plus meaningful equity in a fast-scaling company</li></ul><h3 class="jobSectionHeader"><b>
Details</b></h3><ul><li><b>
Location:</b> San Francisco, CA</li><li><b>
Work policy:</b> On-site &mdash; strictly in-person</li><li><b>
Compensation:</b> $130,000&ndash;$150,000 base (up to $300K total cash comp) + equity</li><li><b>
Visa sponsorship:</b> None available</li><li><b>
Employment type:</b> Full-time</li></ul></div>

Strategic Projects Lead - Coding

<div><p><b>San Francisco, CA &middot; On-site &middot; Full-time</b><br>
<b>Compensation:</b> $180,000&ndash;$220,000 + competitive equity</p><h2 class="jobSectionHeader"><b>
About the Company</b></h2><p>
An early-stage (post&ndash;Series A) company building the training data and evaluation infrastructure that frontier AI labs use to improve their models &mdash; designing high-signal datasets and running rigorous evaluations that go beyond static benchmarks. A small team where individual contributors have direct impact on how the next generation of models learns. The company has raised $30M (~$300M valuation), with a founding team drawn from Jane Street, Citadel, Google, Goldman, and Stanford AI Lab.</p><p>
Founded 2025 &middot; 11&ndash;50 people &middot; Industry: Consumer Tech</p><h2 class="jobSectionHeader"><b>
The Role</b></h2><p>
As a SWE (Environments), you'll design the datasets and evaluation rubrics that directly influence how frontier models learn &mdash; going from hypothesis to live experiment quickly, with output feeding directly into model training runs at scale.</p><p><b>
What you'll be doing</b></p><ul><li>
Design data slices and explore data shapes that expose meaningful model failure modes across domains like finance, code, and enterprise workflows</li><li>
Build and refine evaluation rubrics and reward signals for RLHF and RLVR training pipelines</li><li>
Model annotator behavior and run experiments to improve different model capabilities</li><li>
Develop quantitative frameworks for measuring dataset quality, diversity, and downstream impact on model alignment and capability</li><li>
Create and manage both real-world and synthetic data pipelines</li><li>
Partner with lab research teams to translate their training objectives into concrete data and evaluation specifications</li></ul><p><b>
Tech stack:</b> Not specified</p><h2 class="jobSectionHeader"><b>
Requirements</b></h2><ul><li>
1&ndash;4 years of software engineering experience with strong technical depth</li><li>
Design targeted data slices that surface model failure modes across high-stakes domains (finance, code generation, enterprise workflows)</li><li>
Build and iterate on evaluation rubrics and reward signals powering RLHF and RLVR training pipelines</li><li>
Develop quantitative frameworks to measure dataset quality, diversity, and downstream impact on model alignment and capability</li><li>
Own end-to-end real world and synthetic data pipelines, from scoping with research teams to production-ready evaluation specs</li><li>
Run annotator modeling experiments to improve model capabilities across task types</li></ul><h2 class="jobSectionHeader"><b>
Green Flags</b></h2><ul><li>
Experience at RL environment companies</li><li>
Background in AI safety or benchmarking organizations like METR or Artificial Analysis</li><li>
Genuine obsession with how data structure, selection, and quality drive model behavior</li><li>
Ability to design lightweight experiments and move fast</li><li>
Former founders or early engineers at early stage startups</li><li>
Demonstrated ability to work hard, learn fast, and care deeply about details</li></ul><h2 class="jobSectionHeader"><b>
Red Flags</b></h2><ul><li>
Pure research profile with limited engineering output, this is a SWE role, shipping matters</li><li>
Looking for standard product engineering work &mdash; the real scope is data pipelines, reward modeling, and eval infra</li></ul><h2 class="jobSectionHeader"><b>
Why Join</b></h2><ul><li>
Outsized total cash: base plus substantial profit share, plus competitive equity</li><li>
Direct impact on frontier AI model development, working with the world's leading AI labs</li><li>
High ownership on a small, early team &mdash; scope, build, and ship end to end</li></ul><h2 class="jobSectionHeader"><b>
Details</b></h2><ul><li><b>
Location:</b> San Francisco, CA</li><li><b>
Work policy:</b> On-site</li><li><b>
Compensation:</b> $180,000&ndash;$220,000 + equity</li><li><b>
Visa sponsorship:</b> O-1, OPT</li><li><b>
Employment type:</b> Full-time</li></ul></div>

Software Engineer, RL Environments

<div><p><b>San Francisco, CA &middot; On-site &middot; Full-time</b><br>
<b>Compensation:</b> $120,000&ndash;$300,000 + Competitive Equity</p><h2 class="jobSectionHeader"><b>
About the Company</b></h2><p>
An early-stage, venture-backed FinTech building AI compliance analysts that automate AML, KYC, KYB, and transaction monitoring end-to-end for banks and fintechs. The product operates inside browsers, APIs, and internal systems the way a human analyst would, and is already live with financial institutions across multiple regions.</p><p>
Founded 2024 &middot; Seed stage &middot; Small team &middot; Industry: FinTech</p><h2 class="jobSectionHeader"><b>
The Role</b></h2><p>
A backend-leaning Member of Technical Staff building the end-to-end systems that power production AI compliance workflows &mdash; high-performance infrastructure, reliability, and backend architecture supporting mission-critical automation.</p><p><b>
What you'll be doing</b></p><ul><li>
Architect agent behaviors and build the backend systems behind production AI compliance workflows</li><li>
Build browser agents that navigate legacy systems, portals, and third-party platforms, interpreting unstructured data</li><li>
Process risk signals at the speed money moves &mdash; millions of transactions, sub-second decisions &mdash; via distributed inference, caching, queue orchestration, and self-healing data pipelines on AWS</li><li>
Contribute to an in-house deep-research pipeline that keeps LLMs from conflating similar entities</li><li>
Optimize ML pipelines and ship product features, owning problems vertically</li></ul><p><b>
Tech stack:</b> Python, AWS; browser automation, computer vision, LLM systems.</p><h2 class="jobSectionHeader"><b>
Requirements</b></h2><ul><li>
Experience with backend development and/or ML, especially in Python and AWS</li><li>
Hands-on experience deploying software to production environments</li><li>
Strong communication skills and willingness to interact with clients</li></ul><h2 class="jobSectionHeader"><b>
Green Flags</b></h2><ul><li>
Experience with browser automation and computer vision</li><li>
Background with distributed inference and optimization on AWS</li><li>
Familiarity with LLM systems and deep research pipelines</li><li>
Experience building systems that process millions of transactions at scale</li><li>
Knowledge of compliance, AML, KYC, or financial crime domains</li><li>
Competitive coding background</li><li>
Contributions to open-source projects or personal projects on GitHub</li><li>
Prior experience as a founder or at an early-stage startup</li></ul><h2 class="jobSectionHeader"><b>
Red Flags</b></h2><ul><li>
Candidates from a pure data science background who lack strong technical skills</li><li>
Lack of hands-on experience deploying software to production</li><li>
Primarily academic or research experience without practical engineering work</li></ul><h2 class="jobSectionHeader"><b>
Why Join</b></h2><ul><li>
Build frontier AI agents in production, solving hard problems with no off-the-shelf answers</li><li>
Large, underserved market with real customer traction and measurable impact</li><li>
Small team with wide surface area &mdash; own features end-to-end across backend, ML, and product</li></ul><h2 class="jobSectionHeader"><b>
Details</b></h2><ul><li><b>
Location:</b> San Francisco, CA</li><li><b>
Work policy:</b> On-site</li><li><b>
Compensation:</b> $120,000&ndash;$300,000 + equity</li><li><b>
Visa sponsorship:</b> H-1B, O-1, OPT</li><li><b>
Experience:</b> 1+ years</li><li><b>
Employment type:</b> Full-time</li></ul></div>

Member of Technical Staff

<div><h2 class="jobSectionHeader"><b>Founding Engineer &mdash; Confidential (AI Startup, YC/a16z-Backed)</b></h2><p><b>
Location:</b> San Francisco, CA (Onsite, 5 days/week)<br>
<b>Compensation:</b> $180,000 &ndash; $225,000 base + 1.0% &ndash; 1.5% equity<br>
<b>Visa Sponsorship:</b> Available &mdash; visa transfers supported | Relocation support available<br>
<b>Employment Type:</b> Full-Time</p><h3 class="jobSectionHeader"><b>
About the Company</b></h3><p>
A well-funded AI startup building a new paradigm for software creation &mdash; using AI agents to autonomously create and operate specialized software products at scale. Founded in 2026, the company has raised $5.5M from a16z and other top-tier investors and is building out its founding engineering team of 5&ndash;7 engineers. The founding team has previously scaled companies to $20M ARR.</p><h3 class="jobSectionHeader"><b>
The Role</b></h3><p>
This is a founding engineering role for a generalist full-stack engineer who loves building from zero. You will ship micro apps weekly to real users, encode your processes into increasingly automated workflows, and run rapid experiments with the founding team. All engineers report directly to the founder and CEO.</p><h3 class="jobSectionHeader"><b>
What You'll Own</b></h3><ul><li>
Build and ship micro apps every week with real users, encoding your processes into increasingly automated workflows</li><li>
Work in close collaboration with the founding team</li><li>
Run rapid experiments and decisively double down on what works while cutting what doesn't</li></ul><p><b>
Tech stack:</b> Full-stack, AI &mdash; Python, JavaScript, Kotlin, Go (flexible on language)</p><h3 class="jobSectionHeader"><b>
Requirements</b></h3><ul><li>
1&ndash;5 years of software engineering experience building AI-driven products</li><li>
Experience shipping products or features from ideation to real users with significant traction</li><li>
Proficiency in agentic development &mdash; designing and building orchestration pipelines across multiple agents, tools, and services</li><li>
Full-stack proficiency with a backend focus</li><li>
Active user of modern AI tooling (e.g. Claude Code, Cursor, or similar)</li><li>
At least one clear signal of excellence &mdash; hackathon wins, side projects with significant traction, impressive fellowships, YC founder background, etc.</li><li>
Bachelor's degree in Computer Science or a related technical field</li><li>
Must be based in or willing to relocate to San Francisco</li></ul><h3 class="jobSectionHeader"><b>
Preferred</b></h3><ul><li>
Previous founder or early-stage startup experience &mdash; YC or a16z alum backgrounds a strong plus</li><li>
Degree from a top-tier university (Berkeley, Stanford, CMU, or equivalent)</li></ul><h3 class="jobSectionHeader"><b>
This Role Is NOT For</b></h3><ul><li>
Pretraining or fine-tuning ML researchers &mdash; this is applied agentic engineering, not model training</li><li>
Pure Big Tech careers with no side project, startup, or scrappy chapter</li><li>
Candidates with a pattern of short tenures across multiple companies</li></ul><h3 class="jobSectionHeader"><b>
Interview Process</b></h3><ul><li>
Application review</li><li>
Intro screen (45 min) &mdash; technical depth, past projects, judgment, and founder fit</li><li>
Pair coding session (60 min) &mdash; live coding, no AI tools; CS fundamentals and algorithmic reasoning</li><li>
Onsite (~4 hours) &mdash; agentic coding session, system design, and behavioral/founder-fit conversation</li><li>
Offer</li></ul><h3 class="jobSectionHeader"><b>
Logistics</b></h3><ul><li>
Role is <b>fully onsite in San Francisco (SoMa) &mdash; 5 days/week</b></li><li>
Relocation support available</li><li>
Visa sponsorship available</li></ul><p>
Shortlisted candidates will be contacted by <b>David Joseph &amp; Co.</b>, the recruiting partner managing this search.</p></div>

Founding Engineer — Confidential

Join David Joseph & Company and explore 4   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

David Joseph & Company

About Company

Strategic Projects Lead - Coding

Software Engineer, RL Environments

Member of Technical Staff

Founding Engineer — Confidential