About AIOS

AIOS is building the world’s first full-stack AI doctor.

We’re at $350M ARR, growing from $10M/yr 12 months ago. We’re the world’s fastest growing AI doctor.

We’re faithfully serving >150k/mo patients via Bolt Pharmacy, our main UK brand. We’re profitable.

Our strategy exists at the intersection of two strong theses:

The AI doctor that wins will get to escape velocity using GLP-1s, the fastest growing consumer product in history.
The $2T European healthcare market is overlooked by the most talented builders.

Our master plan:

Step 0 → $100M/yr by end of 2025 : We went from $10M to $100M in 6 months serving the UK GLP-1 market.
Step 1 → $1B ARR by end of 2026 : Over the last 12 months we've grown from 3k to 150k UK active GLP-1 patients. We’ll continue this growth curve to hit $1B ARR.
Step 2 → $10B ARR by end of 2028 : Blitzscale Europe. We’ll be Europe’s largest GLP-1 provider.
Step 3 → $100B/yr by end of 2031 : Get regulatory approval across Europe for our Full Autonomous Prescribing (FAP) system. Win contracts at scale with European payers to mass replace human labor. We’ll be the dominant full-stack AI doctor in Europe.
Step 4 → $1T/yr by end of 2035 : With one line of code and zero human time, you can use AIOS to treat any patient globally with any medication.

In so doing, we’ll become the world’s first trillion-dollar healthcare company.

We’re a young, founder-led company. This is still Day 1 and all our work is ahead of us.

You can read more about working with us here: Working at AIOS

Being a AI Engineering Lead at AIOS

We are building a world-leading Applied AI team.

As AI Engineering Lead at AIOS, your fundamental role is to build the AIOS Agent SDK and make it the foundation for world-class agents across the company.

You are not joining to discover our first AI use case or build another chatbot.

Our customer-facing agent gathers context from across our product and customer history, retrieves the right knowledge, reasons through multi-step cases, and decides when to act, respond, escalate, or stand down. Our agentic workflows autonomously generate >$100k of revenue per day.

This existing harness will become the nucleus of the AIOS Agent SDK. You’ll separate its reusable foundations from its customer-support logic and turn them into a strongly opinionated internal platform.

We’re also building an AI clinical decision-support system. This helps clinicians evaluate patient eligibility, contraindications, dosing, and risk. It will be the second major system built on the SDK and, over time, a foundation for increasingly autonomous clinical decisions.

Once the SDK has proven itself through these two tools, it will become the default foundation for new agents across AIOS.

You’ll be the DRI for agent architecture, model strategy, evals, AI reliability, technical safety, provider relationships, and the shared runtime. You’ll make these decisions autonomously. You’ll ensure we use the best model for each job based on measured quality, reliability, speed, and cost.

This is a technical leadership role. You’ll lead by example as you grow the team.

You’ll ensure:

The AIOS Agent SDK exists and is running the show in production, and it is in exceptionally safe technical hands
Product engineers can build excellent agents without recreating context, tool, safety, eval, and observability infrastructure.
Our agents become more capable without becoming less predictable.
Major changes are supported by trustworthy evidence across quality, reliability, safety, latency, and cost.
Production failures continuously strengthen our evals, architecture, and models.
Our engineers actively seek your judgment and trust the direction you set.
AIOS is clearly an industry leader in applied AI for production healthcare systems.

This is a full-time, fully remote role. You can work async in the timezone of your choice, provided you’re regularly available until midday Pacific Time for collaboration.

This is a senior role. You’ll report directly to Gzim :), (VP of Engineering).

You’ll also work closely with:

Ben Dowdle (Head of Product)
Saim Dalvi (UK Clinical Lead)
Richie Cartwright (CEO)

Key responsibilities

Agent SDK: You’ll turn Jesse’s (customer support tool) existing harness into the strongly opinionated internal platform powering Jesse, Aegis (clinical support tool), and future AIOS agents. You’ll own its architecture, reusable primitives, supported extension points, developer experience, and integration with our existing infrastructure.
Jesse & Aegis: You’ll become the senior technical owner of Jesse and work closely with the engineers and Clinical Product team building Aegis. You’ll improve both systems while extracting the shared foundations they need across context, retrieval, memory, orchestration, tools, state, and escalation.
Evals & Experimentation: You’ll build trustworthy benchmarks using deterministic checks, simulations, model-based graders, human judgment, and production outcomes. You’ll establish the path from offline evaluation to controlled production experiments so major changes ship with evidence.
Production Learning Loop: You’ll turn traces, poor resolutions, escalations, incidents, tool failures, and successful outcomes into better evals, stronger architecture, improved models, and permanent platform capabilities.
Safety & Compliance: You’ll make consequential agent actions safe through authorization, validation, idempotency, auditability, recovery, and human handoff. You’ll encode compliance, privacy, security, and regional requirements into the platform wherever possible.
Models & Economics: You’ll own model selection, routing, fallbacks, caching, and our ~$200k monthly model spend. When the evidence supports it, you’ll lead the data preparation, fine-tuning, evaluation, and AIOS-controlled deployment of specialized open-weight models.
Reliability: You’ll own the shared runtime in production, including tracing, observability, testing, provider resilience, capacity, and incident response. You’ll be the senior engineering DRI when an AI system behaves unsafely, quality regresses, or the platform fails.
Technical Leadership: You’ll set AIOS’s AI architecture and strategy in close partnership with the VP of Engineering. You’ll make the final call on major technical decisions, guide engineers across product pods, and remain hands-on by writing production code and personally building the most important foundations.
Build the Team: You’ll inherit one engineer and build the Applied AI team to approximately five exceptional people during your first year. You’ll own our technical relationships with leading model providers and represent AIOS externally where doing so strengthens our work.

Need to have

Experience: You have 8+ years of software engineering experience and remain an active production contributor.
Education: You have at least a bachelor’s degree in Computer Science, Machine Learning, or a closely related technical field.
Production Agents: You have personally built and shipped an exceptional agentic system used by real customers. It did more than answer questions: it reasoned across multiple steps, used tools, changed state, and operated under real production constraints.
Agent Architecture: You can reason deeply about harnesses, orchestration, context construction, retrieval, memory, state, tool design, structured workflows, and error recovery.
Evals: You’ve built or meaningfully owned evaluation systems for probabilistic products. You understand dataset construction, evaluator design, simulations, regression detection, noisy metrics, and the relationship between offline performance and production outcomes.
Software Engineering: You have strong systems-engineering fundamentals. You can reason about APIs, distributed systems, concurrency, queues, databases, observability, failure modes, and production reliability.
Consequential Actions: You know how to let an agent act safely. You have strong judgment around authorization, validation, idempotency, state transitions, auditability, recovery, and escalation.
Model Judgement: You understand the capabilities and limitations of current frontier and open-weight models. You know when the model is the problem and when the real problem is context, tools, data, orchestration, or evaluation.
Open-Weight Models: You have enough technical depth to lead the fine-tuning and AIOS-controlled deployment of open-weight models when the evidence supports doing so. Prior production deployment is not required.
Leadership: You have successfully led and managed a small technical engineering team. You set a clear direction, raise the quality bar, develop strong engineers, and address underperformance.
Technical Authority: Strong engineers trust your judgment. You can make difficult decisions, explain the trade-offs clearly, and push back without hesitation when a proposed approach is unsound.
Communication: You can explain difficult technical ideas to engineers, product leaders, clinicians, and executives without flattening the important details.
Independence: You create clarity in ambiguous environments and make high-quality decisions without hand-holding.
Builder: You still write production code. You lead from inside the work rather than managing it from a distance.
Ownership: When quality drops, costs spike, tools fail, or providers degrade, you take responsibility for reaching the outcome rather than identifying whose component was technically at fault.

Nice to have

Agent Platforms: You’ve built runtimes, SDKs, harnesses, tool layers, evaluation platforms, or shared AI infrastructure used by other engineers.
Customer Agents: You’ve built high-volume customer-service, commerce, or transactional agents operating across complex, multi-step customer journeys.
High-Stakes Systems: You’ve worked on healthcare, financial, insurance, or other systems where correctness, traceability, and careful rollout matter.
Model Adaptation: You’ve fine-tuned, distilled, evaluated, or deployed an open-weight model for a specific production workflow.
Long-Term Memory: You’ve built durable memory, context compression, personalization, or agents operating across sessions and extended periods.
Real-Time Systems: You’ve worked on voice agents, streaming systems, or other latency-sensitive AI experiences.
Provider Relationships: You’ve worked directly with frontier model providers on evaluations, technical issues, capacity, pricing, or early access.
Talent: You have a strong nose for exceptional AI engineers and know how to create an environment in which they do their best work.
Research Fluency: You can translate relevant research into reliable production systems without confusing novelty with progress.
Figure It Out: You can move from debugging a production trace, to redesigning an eval, to reviewing an agent abstraction, to handling a provider incident.

Our cultural standards

We aim to make this your life’s work. This should be the most challenging, most rewarding role of your life. Accordingly, these are the core cultural standards to which we hold ourselves & our team-members:

Belief in the mission: We will have served 100 million patients by the end of 2035 and we transform the life of most patients who join. We have a lot of work to do. We are obsessed with our patients and are dedicated to the mission.
Unwavering integrity: We are at the frontier, so we often live in ambiguity with no trodden path. When we can’t look to others for guidance, we must maintain impeccable ethics and unwavering integrity.
Only the paranoid survive: Bad sh*t is coming. By joining us, you’re choosing to sail straight towards the storms with unhesitating conviction. However much we’ve already done, however far we’ve already come — it’s still Day 1 and all our work is ahead of us.
If we’re average we fail: We are only interested in “insanely great”, a focus on the quality of our execution that in everyday life would be considered pathological. We have a dedication to excellence and reject incompetence.
Commitment to candor: That which can be destroyed by the truth should be. You get full transparency from the company and the company expects full transparency from you. We never say anything about someone that we wouldn’t say to them directly. We give feedback with love and do not need to protect people from fleeting physical sensations.
A maniacal sense of urgency: We execute at an intensity that most people think is impossible. Speed is critical and we need things done yesterday. We all work very hard and in such a competitive world there really is no other way to win.
Enduring frugality: We are frugal. We hate being wasteful and we are anti-luxury. A culture of cheapness keeps us young. We spend our cash wisely & carefully — in a way that would make our grandmas proud.
Bulldozing barriers: The world is malleable and we shape it. We truly believe this and act accordingly. We are relentlessly resourceful and are at the mercy of no-one but ourselves. You’ll be shocked how capable you are and how much you can achieve.
Keep your head down: We’re boring people doing exciting work. We don’t chase short-term status — we ignore short-term dopamine hits and focus on what matters. Outsiders will underestimate us and we revel in that.
The power of focus: We live in a world of power laws and we cannot overestimate the unimportance of practically everything. Know your One Thing, and nail it.

🎯 _“You just build a f*_ing amazing experience. Make each step amazing. Make every decision in the long term interest of the customer. Give the customer massively more value than you take.”

Compensation & Benefits

You get paid above market salary and you get early stage equity, so you get really rich if we nail this.

Compensation: $200k-$400k/yr, + equity

Benefits

The stuff below is cool as well.

Healthcare: comprehensive medical insurance (if appropriate).
Vacation: PTO with a yearly minimum (≥2wks/yr + local national holidays)
Personal development: budget for books, courses, coaching.
Personal wellness: budget for gym, health apps.
GLP-1s: free membership with a clinic offering GLP-1s.
Equipment: Macbook & work-from-home equipment provided as needed.
What are we missing? We're still early so you get to shape our culture.

How to apply

Apply on Ashby

Remote Software Engineer New Grad Machine Learning Platform Quora Remote Jobs

Find Your Next Role

640 Open Positions

Remote Software Engineer New Grad Machine Learning Platform Quora Remote Salary Ranges

Companies Hiring for Remote Software Engineer New Grad Machine Learning Platform Quora Remote Roles

Common Remote Software Engineer New Grad Machine Learning Platform Quora Remote Job Titles

Remote Software Engineer New Grad Machine Learning Platform Quora Remote Salary Ranges1931

Companies Hiring for Remote Software Engineer New Grad Machine Learning Platform Quora Remote Roles8

Common Remote Software Engineer New Grad Machine Learning Platform Quora Remote Job Titles8