Founding AI Engineer (YC W24) w/ .25% - 75% Equity
Bounty Amount: $9,000-$13,500
Company Name: Sonia
Role Type: Full-time
Location: San Francisco, CA (in-person)
Salary / Hourly Rate: $120,000 - $180,000 per year
Benefits: In-person SF team; high ownership on a 5-person, seed-stage startup.,Meaningful equity; fast path to scope as the product/function owner.,US Citizens Only,Open to Exceptional New Grads
Role Information
Role Overview: N/A
Responsibilities: Ship end-to-end LLM features for voice + text therapy sessions: prompt/agent design, tool use/function calling, latency & turn-taking handling, and production deployment., Build offline and online eval loops (unit tests, regression suites, shadow/prod checks) that track reliability and user outcomes (e.g., anxiety-score trends like GAD-7), and use them to decide what ships., Implement and iterate safety systems: risky-response detection, fallback/deferral strategies, human-in-the-loop escalation, and post-incident reviews; treat safety as a first-class product feature., Own Python services and lightweight product surfaces (internal tools, small UX hooks) that speed up experimentation and founder feedback loops., Partner with Design (voice/chat UX) and Clinical Research to translate findings into product improvements and safeguards; instrument what you ship so we can learn quickly in production., Drive a weekly shipping cadence: prototype → evaluate → harden → release; document decisions and metrics so the team can build on them.
Qualifications: Strong Python plus hands-on prompt/LLM engineering (tool use, function calling, retrieval or memory patterns, evals); you’ve shipped something real users touched., Product sense and speed: you can simplify ambiguous problems, choose pragmatic baselines, and deliver value in days—not quarters., Track record of safety-critical thinking (red-flag detection, guardrails, fallback paths) and comfort being accountable for quality in production., Evidence-driven mindset: you instrument features and are comfortable tying quality to measurable outcomes (not just engagement)., Collaboration in a tiny, high-trust team: you like building in person with founders and cross-functional partners (design/research). In-person, San Francisco required; w/ US work authorization (with no sponsorship needs)
Minimum Requirements: In-person, San Francisco (team works on-site). (From founder email + YC page),US work authorization (YC lists “US citizen/visa only”).,Strong Python & Swift Mobile Development,Evidence of shipped LLM/agent features (code or live demo).,Safety + eval mindset (guardrails, pre-delivery checks) given the mental-health context
Screening Questions: (Optional Video). This step is completely optional. If you’d like, record a short 2–3 minute video introducing yourself and your experience — or share a recording of your interview with the recruiter if that’s easier. You can upload the link via Loom or Google Drive. This just helps us get to know you better, but there’s no pressure if you’d prefer to skip it.,(Optional Portfolio / GitHub) If available, please share a link to your GitHub, portfolio, or any recent projects you’ve worked on. This is entirely optional but helps provide more context about your work.,Why Sonia? What about our mission (building a safe AI therapist, voice + text) and our in-person SF culture resonates with you?
Company Information
About Company: N/A
Culture: N/A
Additional Information
Interview Process: Step 1: Vibe check call — 15 minsQuick intro, alignment on the mission and role, confirm in-person SF and work-auth fit.Step 2: Technical take-home — ~4 hours (compensated)Build a small LLM feature or eval pipeline relevant to voice + text therapy (prompt/agent design, tool use/function calling, safety checks). Include notes on trade-offs and what you’d test next. Step 3: Technical deep-dive & code review — 30–45 minsWalk through your take-home and 1–2 shipped LLM projects. We’ll dig into prompts, evals, guardrails, latency/turn-taking handling, and how you measured quality.Step 4: In-person trial in SF — 1–2 days (paid)Work on a scoped feature with the founders: prototype → evaluate → harden → ship. We look for clarity, speed, product sense, and how you reason about safety and measurable outcomes. (Team works on-site; trials are in San Francisco.)Step 5: OfferFast debrief and references as needed; discuss compensation/equity within YC-listed ranges for this role.
Day to day: Design, build, and ship end-to-end LLM features that power Sonia’s voice + text therapy sessions. You’ll iterate on prompts/agents, wire in tool use/function calling, stand up offline/online eval loops, and harden safety guardrails before releasing to production. Expect a fast idea → prototype → evaluate → ship cadence with founders, and instrumentation that ties quality to real outcomes (e.g., reliability and early GAD-7 movement the team tracks).
Team: Work directly with the three founders on a ~5-person team in person in San Francisco. You’ll pair with design on voice/chat UX and with research on measurement and risk mitigation, keeping feedback loops tight and decisions pragmatic. (YC lists skills as Prompt Engineering, Python; the culture emphasizes on-site collaboration.)
Growth: As one of the first engineers, you’ll define technical standards for LLM quality, evals, and safety, influence architecture choices, and build internal tooling that speeds experimentation. As the product and team scale, there’s scope to lead major lines (e.g., new session modalities, memory/eval systems), mentor future hires, and help formalize practices that keep Sonia outcome-first and safe—consistent with the company’s “develop it like a drug” mindset.
Ideal Candidate Profile: We’re looking for a design–engineering hybrid who owns discovery → UX/UI → implementation for our iOS app, iterates quickly with the founders in person in San Francisco, and cares deeply about measurable outcomes and safety.What makes you a strong fit • You’ve shipped mobile product end-to-end (portfolio shows discovery, design, and hands-on build), ideally in Swift/SwiftUI. • You can design stateful conversational experiences (voice + chat) and instrument what you ship to learn quickly. • You use research and data to decide—e.g., you can explain how you’d evaluate changes with validated measures like GAD-7, not just engagement metrics. • You thrive on small-team pace and high ownership, collaborating daily with founders in person in SF. • You treat safety as a product feature and can describe guardrails you’ve designed for sensitive contexts. Benchmark profile (from founders) • Design: young, hungry, ideally with some engineering skills or interest; new-grad OK. • https://x.com/floguo (design engineer; strong product taste + build skills).Signals we’re likely to pass • Only visual polish with no shipped, user-validated work. • Can’t work in person in San Francisco. • No experience designing or building for voice/chat or other safety-critical UX.Why this is exciting • Mission with evidence: Sonia is building a safe AI therapist (voice + text) and publicly emphasizes outcomes; you’ll shape how the app looks, feels, and measures progress from day one.
Founding AI Engineer (YC W24) w/ .25% - 75% Equity
San Francisco, CA (in-person)
Full-time
Est. Fee
$9,000-$13,500
Salary Range
$120,000 - $180,000 per year
Job Details
Job Overview
Transform cutting-edge research into reliable, user-visible AI features in a mental health context. This role focuses on turning prompts into production-ready end-to-end LLM features for voice and text therapy sessions, prioritizing safety and evaluation to ensure quality outcomes.
Key Responsibilities: Design and deploy LLM features for therapy, manage offline and online evaluation loops, implement safety systems, and drive a weekly prototype to release cadence.
Required Technical Skills:...
Responsibilities
You’ll be the force-multiplier who turns research and product ideas into reliable, safe, user-visible features—fast. Day to day you’ll design prompts/agents, wire in tools, build evals and safety guardrails, and ship to production with the founders, always tying quality to real outcomes. (NEW GRADS OKAY)
Ship end-to-end LLM features for voice + text therapy sessions: prompt/agent design, tool use/function calling, latency & turn-taking handling, and production deployment.
Build offline and online eval loops (unit tests, regression suites, shadow/prod checks) that track reliability and user outcomes (e.g., anxiety-score trends like GAD-7), and use them to decide what ships.
Implement and iterate safety systems: risky-response detection, fallback/deferral strategies, human-in-the-loop escalation, and post-incident reviews; treat safety as a first-class product feature.
Own Python services and lightweight product surfaces (internal tools, small UX hooks) that speed up experimentation and founder feedback loops.
Partner with Design (voice/chat UX) and Clinical Research to translate findings into product improvements and safeguards; instrument what you ship so we can learn quickly in production.
Drive a weekly shipping cadence: prototype → evaluate → harden → release; document decisions and metrics so the team can build on them.
Qualifications
Sonia optimizes for builders who have actually shipped LLM systems and love the loop of design → measurement → iteration, in a small, in-person SF team.
Strong Python plus hands-on prompt/LLM engineering (tool use, function calling, retrieval or memory patterns, evals); you’ve shipped something real users touched.
Product sense and speed: you can simplify ambiguous problems, choose pragmatic baselines, and deliver value in days—not quarters.
Track record of safety-critical thinking (red-flag detection, guardrails, fallback paths) and comfort being accountable for quality in production.
Evidence-driven mindset: you instrument features and are comfortable tying quality to measurable outcomes (not just engagement).
Collaboration in a tiny, high-trust team: you like building in person with founders and cross-functional partners (design/research). In-person, San Francisco required; w/ US work authorization (with no sponsorship needs)
Ideal Candidate
We’re looking for a design–engineering hybrid who owns discovery → UX/UI → implementation for our iOS app, iterates quickly with the founders in person in San Francisco, and cares deeply about measurable outcomes and safety.
What makes you a strong fit
• You’ve shipped mobile product end-to-end (portfolio shows discovery, design, and hands-on build), ideally in Swift/SwiftUI.
• You can design stateful conversational experiences (voice + chat) and instrument what you ship to learn quickly.
• You use research and data to decide—e.g., you can explain how you’d evaluate changes with validated measures like GAD-7, not just engagement metrics.
• You thrive on small-team pace and high ownership, collaborating daily with founders in person in SF.
• You treat safety as a product feature and can describe guardrails you’ve designed for sensitive contexts.
Benchmark profile (from founders)
• Design: young, hungry, ideally with some engineering skills or interest; new-grad OK.
• Only visual polish with no shipped, user-validated work.
• Can’t work in person in San Francisco.
• No experience designing or building for voice/chat or other safety-critical UX.
Why this is exciting
• Mission with evidence: Sonia is building a safe AI therapist (voice + text) and publicly emphasizes outcomes; you’ll shape how the app looks, feels, and measures progress from day one.
Must-Have Requirements
In-person, San Francisco (team works on-site). (From founder email + YC page)
US work authorization (YC lists “US citizen/visa only”).
Strong Python & Swift Mobile Development
Evidence of shipped LLM/agent features (code or live demo).
Safety + eval mindset (guardrails, pre-delivery checks) given the mental-health context
Screening Questions
1. (Optional Video). This step is completely optional. If you’d like, record a short 2–3 minute video introducing yourself and your experience — or share a recording of your interview with the recruiter if that’s easier. You can upload the link via Loom or Google Drive. This just helps us get to know you better, but there’s no pressure if you’d prefer to skip it.
2. (Optional Portfolio / GitHub) If available, please share a link to your GitHub, portfolio, or any recent projects you’ve worked on. This is entirely optional but helps provide more context about your work.
3. Why Sonia? What about our mission (building a safe AI therapist, voice + text) and our in-person SF culture resonates with you?
Sonia’s mission is to build a safe AI therapist that can match the effectiveness of a top (99th-percentile) human therapist and make high-quality mental-health support available to anyone. The product conducts complete therapy sessions via voice and text in a mobile app and draws on structured approaches such as CBT alongside short, timely check-ins.
After a year of exploring different architectures and form factors, the team reports a recent breakthrough and early evidence of significant clinical impact, including measurable reductions in GAD-7 anxiety scores after roughly two weeks of use. Sonia frames progress and product decisions around outcomes and safety, not just engagement.
The company publicly emphasizes a “drug-like” development mindset—rigorous evaluation, safeguards, and continuous testing as they scale access—reflecting a commitment to real-world efficacy and responsible deployment.
Company Culture
Sonia operates with a builder-scientist culture: small team, high ownership, and rapid iteration paired with rigorous safety and evaluation. Everyone is expected to move ideas from prototype to production quickly while holding a high bar for clinical quality and user protection.
The team is outcome-first. Success is defined by improvements in validated mental-health measures (like GAD-7) and by user well-being, not by vanity metrics. Experiments are instrumented, results are measured, and learning cycles are fast.
Safety is treated as a product feature. Guardrails and review processes are built into the experience from the start, consistent with the company’s public stance that developing an AI therapist should follow a process closer to drug development than typical consumer app iteration.
The environment favors kindness, intensity, and clear thinking. Team members collaborate closely with founders, talk to users, and ship high-quality work that directly advances access to effective mental-health support. Sonia is San-Francisco-based and works together in person, per the founders’ note you shared; their open roles are listed for San Francisco.
Benefits
Retirement/401k
Health Insurance
Vision Insurance
Dental Insurance
In-person SF team; high ownership on a 5-person, seed-stage startup.
Meaningful equity; fast path to scope as the product/function owner.
US Citizens Only
Open to Exceptional New Grads
Relocation & Sponsorship
Relocation Assistance
Visa Sponsorship
What you can expect
Day to Day
Design, build, and ship end-to-end LLM features that power Sonia’s voice + text therapy sessions. You’ll iterate on prompts/agents, wire in tool use/function calling, stand up offline/online eval loops, and harden safety guardrails before releasing to production. Expect a fast idea → prototype → evaluate → ship cadence with founders, and instrumentation that ties quality to real outcomes (e.g., reliability and early GAD-7 movement the team tracks).
Team
Work directly with the three founders on a ~5-person team in person in San Francisco. You’ll pair with design on voice/chat UX and with research on measurement and risk mitigation, keeping feedback loops tight and decisions pragmatic. (YC lists skills as Prompt Engineering, Python; the culture emphasizes on-site collaboration.)
Growth
As one of the first engineers, you’ll define technical standards for LLM quality, evals, and safety, influence architecture choices, and build internal tooling that speeds experimentation. As the product and team scale, there’s scope to lead major lines (e.g., new session modalities, memory/eval systems), mentor future hires, and help formalize practices that keep Sonia outcome-first and safe—consistent with the company’s “develop it like a drug” mindset.
Interview Process
Step 1: Vibe check call — 15 mins
Quick intro, alignment on the mission and role, confirm in-person SF and work-auth fit.
Build a small LLM feature or eval pipeline relevant to voice + text therapy (prompt/agent design, tool use/function calling, safety checks). Include notes on trade-offs and what you’d test next.
Step 3: Technical deep-dive & code review — 30–45 mins
Walk through your take-home and 1–2 shipped LLM projects. We’ll dig into prompts, evals, guardrails, latency/turn-taking handling, and how you measured quality.
Step 4: In-person trial in SF — 1–2 days (paid)
Work on a scoped feature with the founders: prototype → evaluate → harden → ship. We look for clarity, speed, product sense, and how you reason about safety and measurable outcomes. (Team works on-site; trials are in San Francisco.)
Step 5: Offer
Fast debrief and references as needed; discuss compensation/equity within YC-listed ranges for this role.
Companies to Source From
These companies are similar to our client. Candidates with experience at these companies are seen as a big plus.
Springhealthspringhealth.com
Lyrahealthlyrahealth.com
Modernhealthmodernhealth.com
Headwayheadway.co
Growtherapygrowtherapy.com
Sondermindsondermind.com
Helloalmahelloalma.com
Charliehealthcharliehealth.com
Concerthealthconcerthealth.com
Brightsidebrightside.com
Talkspacetalkspace.com
Betterhelpbetterhelp.com
Cerebralcerebral.com
Headspaceheadspace.com
Calmcalm.com
Meruhealthmeruhealth.com
Woebothealthwoebothealth.com
Youperyouper.ai
Kintsugihealthkintsugihealth.com
Hellobrightlinehellobrightline.com
Linearlinear.app
Notionnotion.so
Arcarc.net
Superhumansuperhuman.com
Framerframer.com
Mercurymercury.com
Rampramp.com
Hexhex.tech
Pitchpitch.com
Figmafigma.com
Humehume.ai
Polypoly.ai
Elevenlabselevenlabs.io
Soundhoundsoundhound.com
Speechifyspeechify.com
Synthflowsynthflow.ai
Cekuracekura.ai
Vapivapi.ai
Retellretell.ai
Sondehealthsondehealth.com
Canaryspeechcanaryspeech.com
Wysawysa.com
Additional Information
Additional Information
Overview
Sonia is building a safe AI therapist designed to be as effective as a top (99th-percentile) human therapist and to make high-quality mental-health support broadly accessible. The product delivers full therapy sessions by voice and by text in an iOS app, and the team reports early GAD-7 anxiety-score reductions after ~2 weeks of use. Sonia treats safety and clinical efficacy as first-class product requirements.
The company
Seed-stage, ~5-person team based in person in San Francisco (YC W24). The founders are hands-on and move quickly from prototype to production, with tight loops between design, engineering, and research. Sonia has raised ~$3.5M from YC, Moonfire, and notable angels (e.g., founders of Verkada, Reddit, Instacart).
The why
Millions struggle to access timely, effective therapy. Sonia’s bet is that carefully-designed conversational interfaces—especially voice—plus rigorous evaluation can expand access without compromising outcomes. The team explicitly frames development more like drug development than a typical consumer app: ship quickly, measure real-world effect, and harden safety guardrails as scale grows. If successful, this could put high-quality support in everyone’s pocket.
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Relocation & Sponsorship
Relocation Assistance
Visa Sponsorship
Must-Have Requirements
In-person, San Francisco (team works on-site). (From founder email + YC page)
US work authorization (YC lists “US citizen/visa only”).
Strong Python & Swift Mobile Development
Evidence of shipped LLM/agent features (code or live demo).
Safety + eval mindset (guardrails, pre-delivery checks) given the mental-health context
Screening Questions
1. (Optional Video). This step is completely optional. If you’d like, record a short 2–3 minute video introducing yourself and your experience — or share a recording of your interview with the recruiter if that’s easier. You can upload the link via Loom or Google Drive. This just helps us get to know you better, but there’s no pressure if you’d prefer to skip it.
2. (Optional Portfolio / GitHub) If available, please share a link to your GitHub, portfolio, or any recent projects you’ve worked on. This is entirely optional but helps provide more context about your work.
3. Why Sonia? What about our mission (building a safe AI therapist, voice + text) and our in-person SF culture resonates with you?
Benefits
Retirement/401k
Health Insurance
Vision Insurance
Dental Insurance
In-person SF team; high ownership on a 5-person, seed-stage startup.
Meaningful equity; fast path to scope as the product/function owner.
US Citizens Only
Open to Exceptional New Grads
Login & Apply to View More
Sign in to your account to access full job details and apply.
Companies to Source From
These companies are similar to our client. Candidates with experience at these companies are seen as a big plus.
Springhealthspringhealth.com
Lyrahealthlyrahealth.com
Modernhealthmodernhealth.com
Headwayheadway.co
Growtherapygrowtherapy.com
Sondermindsondermind.com
Helloalmahelloalma.com
Charliehealthcharliehealth.com
Concerthealthconcerthealth.com
Brightsidebrightside.com
Talkspacetalkspace.com
Betterhelpbetterhelp.com
Cerebralcerebral.com
Headspaceheadspace.com
Calmcalm.com
Meruhealthmeruhealth.com
Woebothealthwoebothealth.com
Youperyouper.ai
Kintsugihealthkintsugihealth.com
Hellobrightlinehellobrightline.com
Linearlinear.app
Notionnotion.so
Arcarc.net
Superhumansuperhuman.com
Framerframer.com
Mercurymercury.com
Rampramp.com
Hexhex.tech
Pitchpitch.com
Figmafigma.com
Humehume.ai
Polypoly.ai
Elevenlabselevenlabs.io
Soundhoundsoundhound.com
Speechifyspeechify.com
Synthflowsynthflow.ai
Cekuracekura.ai
Vapivapi.ai
Retellretell.ai
Sondehealthsondehealth.com
Canaryspeechcanaryspeech.com
Wysawysa.com
Founding AI Engineer (YC W24) w/ .25% - 75% Equity - Bounty Position
Company: Sonia
Location: San Francisco, CA (in-person)
Employment Type: Full-time
Salary: $120,000 - $180,000 per year
Bounty Amount: $9,000-$13,500
Transform cutting-edge research into reliable, user-visible AI features in a mental health context. This role focuses on turning prompts into production-ready end-to-end LLM features for voice and text therapy sessions, prioritizing safety and evaluation to ensure quality outcomes. Key Responsibilities: Design and deploy LLM features for therapy, manage offline and online evaluation loops, implement safety systems, and drive a weekly prototype to release cadence. Required Technical Skills:...
