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ai engineer - learn engine: intelligence & optimization Jobs in San Francisco

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ai engineer, ai & data platforms (aidp)

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principal ai engineer

Ontrac Solutions

<div><h1 class="jobSectionHeader">Overview</h1>
We are seeking a Principal GenAI Architect / Forward Deployed Principal Engineer to lead the design, delivery, and productionization of enterprise-grade Generative AI solutions within a highly regulated banking environment. This role will partner directly with business, product, engineering, architecture, risk, cyber, legal, compliance, and model governance teams to translate high-impact financial services use cases into scalable, secure, and compliant AI systems.
The ideal candidate has deep experience designing and delivering production-scale GenAI solutions across enterprise environments, with strong exposure to banking, financial services, risk management, customer operations, regulatory controls, and data protection requirements. This person will serve as a recognized GenAI expert across the organization, helping define reusable patterns, influence platform roadmaps, and raise the technical bar for responsible AI adoption across lines of business.
<h2 class="jobSectionHeader">Key Responsibilities</h2>
<h3 class="jobSectionHeader">GenAI Architecture &amp; Production Readiness</h3>
Own and define enterprise-grade GenAI architectures for banking and financial services use cases, including RAG pipelines, agentic workflows, prompt orchestration, and multi-model routing strategies.
Drive production readiness for GenAI solutions, ensuring scalability, resiliency, observability, latency optimization, security, and cost efficiency.
Lead complex architectural decisions across data ingestion, vector databases, model selection, guardrails, API scalability, performance optimization, and secure integration with banking systems.
Establish reference architectures, reusable patterns, and best practices to accelerate responsible GenAI adoption across lines of business.
Partner with central AI platform teams to align solution architecture with enterprise AI services, platform capabilities, banking technology standards, and long-term roadmap priorities.
<h3 class="jobSectionHeader">Banking Use-Case Delivery</h3>
Act as a Forward Deployed Principal Engineer, partnering directly with business, product, and engineering teams to deliver high-impact GenAI use cases from ideation through production.
Translate banking and financial services business problems into clear AI system designs, technical requirements, and non-functional requirements with measurable outcomes.
Support GenAI use cases across areas such as customer service, operations, knowledge management, risk, compliance, fraud, employee productivity, document intelligence, and internal workflow automation.
Troubleshoot and resolve complex issues across non-production and production environments.
Partner closely with application teams to ensure AI solutions integrate effectively into existing banking platforms, enterprise workflows, data environments, APIs, and control frameworks.
Influence platform roadmap by feeding real-world banking use-case requirements back into central AI services and enterprise AI platform teams.
<h3 class="jobSectionHeader">Governance, Risk &amp; Compliance</h3>
Ensure all AI solutions align with banking risk, cyber, model governance, data protection, privacy, and regulatory expectations.
Partner with Cyber, Model Risk Management, Legal, Compliance, Risk, and Data Governance teams to design compliant AI patterns without slowing delivery.
Embed security, privacy, responsible AI, ethical AI, explainability, human oversight, and auditability into solution design by default.
Help define practical implementation patterns that balance innovation, speed, governance, regulatory expectations, and enterprise control requirements.
Ensure GenAI solutions are designed with appropriate guardrails for sensitive financial data, customer information, personally identifiable information, and regulated business processes.
<h3 class="jobSectionHeader">Organizational Influence &amp; Mentorship</h3>
Serve as a recognized GenAI expert across the enterprise, regularly consulted by engineering, architecture, product, risk, compliance, and leadership teams.
Mentor senior and staff-level engineers and help raise the technical bar across banking technology teams.
Contribute to internal communities of practice, architecture reviews, executive-level technical discussions, AI governance forums, and knowledge-sharing sessions.
Represent enterprise GenAI capabilities in internal innovation forums, banking technology discussions, and responsible AI showcases.
<h2 class="jobSectionHeader">Required Qualifications</h2>
7+ years of software engineering experience, with significant depth in AI/ML, data-intensive systems, distributed systems, or enterprise-scale platforms.
2+ years of hands-on Python programming experience.
2+ years of experience designing and delivering production-scale Generative AI systems in an enterprise environment.
2+ years of experience with LLMs, prompt engineering, and RAG architecture.
2+ years of experience with vector databases, semantic search, and retrieval systems.
2+ years of experience with API-driven, cloud-native architectures.
2+ years of experience with distributed systems, performance optimization, scalability, and reliability engineering.
Experience working within banking, financial services, fintech, or another highly regulated enterprise environment.
<h2 class="jobSectionHeader">Preferred Qualifications</h2>
Strong understanding of banking technology environments and non-functional requirements, including security, scalability, resiliency, observability, latency, auditability, and cost management.
Demonstrated Principal-level impact, with influence across multiple teams, platforms, business units, or lines of business.
Experience operating in highly regulated environments, with financial services or banking experience strongly preferred.
Hands-on experience with agentic AI frameworks, AI workflow orchestration, and multi-model routing.
Prior experience in a Forward Deployed Engineer, embedded engineering, or business-facing technical delivery model.
Experience partnering with risk, cyber, legal, compliance, data governance, or model governance teams to deliver production AI solutions.
Familiarity with banking controls, customer data protection, model risk management, audit requirements, regulatory expectations, and responsible AI principles.
Ability to communicate complex technical concepts clearly to senior executives, technical stakeholders, risk partners, compliance teams, and non-technical business leaders.
<h2 class="jobSectionHeader">Ideal Candidate Profile</h2>
The ideal candidate is a hands-on Principal-level engineer and architect who can move seamlessly between strategy, architecture, and execution in a banking environment. They are comfortable working directly with business teams to understand real-world financial services problems, while also going deep with engineering teams on system design, performance, security, governance, and production readiness.
This person brings strong technical judgment, enterprise banking delivery experience, and the ability to build practical, compliant GenAI solutions that can scale responsibly across a large financial institution.</div>

Principal AI Engineer

Smvsoft LLC

Founding Engineer - Applied AI San francisco, CA (Full time)- In-Office$180k-$230k per annumNO C2CAbout the RoleHiring a world-class Applied AI Engineer to build the core systems behind their automation engine for hardware engineering.This is a deeply technical, high-impact role. You will be among the first technical hires and will own mission-critical systems end-to-end. The problems are ambiguous, the constraints are real, and the expectations are high. If you move fast from idea to production, care deeply about customer experience, and want to build foundational AI infrastructure for the world's most impactful industries, this role is for you.Key Responsibilities<ul><li>Design and implement core workflows and infrastructure for hardware engineering agents, including intelligent context management, novel indexing approaches, and post-training</li><li>Build agents and ML models that can interpret, reason over, and manipulate complex engineering design data, integrating with enterprise-grade engineering tools and systems</li><li>Work closely with customers and the engineering team to deliver AI-powered workflows that are reliable, intuitive, and trusted in production environments</li><li>Prototype rapidly, validate ideas with real users, and ship frequently</li><li>Influence engineering culture, architecture decisions, and the future of the product</li></ul>RequirementsMust-Have<ul><li>Bachelor's or higher in Computer Science, Machine Learning, or equivalent experience</li><li>Strong familiarity with LLM architectures and agent research trends</li><li>Excellent programming skills with experience using ML libraries such as PyTorch, Hugging Face, and W&amp;B</li><li>Experience building production ML or AI systems</li><li>Solid practical experience with search and information retrieval</li><li>Moves fast from idea to production, with a genuine care for customer experience</li><li>Based in or willing to relocate to San Francisco, or an exceptional remote candidate</li></ul>Nice-to-Have<ul><li>2+ years in applied machine learning, backend engineering, or AI infrastructure</li><li>Experience working with machine learning over geometric data, including CAD</li><li>Track record of high-impact contributions or published papers at top-tier AI labs or teams</li></ul>Pay: $180,000.00 - $230,000.00 per yearWork Location: In person

Founding Engineer - Applied AI

Hellyeah AI

AI Engineer - Learn Engine: Intelligence &amp; OptimizationLocation: San Francisco HQ; ShanghaiAddress: San Francisco, CaliforniaEmployment Type: Full timeLocation Type: HybridDepartment: EngineeringCompensation: San Francisco $200K - $1M + 0.5% - 3% equityBuild the brain of an autonomous growth OS. The system you create will manage millions in ad spend and get measurably smarter with every dollar. This is the moat: every competitor has humans optimizing campaigns manually. You are building the intelligence layer that compounds. The Platform engineer creates the tools; you create the decisions. Together you build something nobody else has.Must Have- Has built recommendation, optimization, or decision systems where outputs improve future inputs.- Strong statistical reasoning and experimentation judgment under noisy real-world data.- Strong LLM orchestration or agent-system experience for reasoning over campaign context.- Can design optimization policies, scoring systems, or automated recommendation loops.- AI-first development workflow and ability to ship production systems quickly.Nice to Have- Ad-tech optimization patterns: bid management, budget allocation, ROAS optimization.- Reinforcement learning experience.- Hyperparameter optimization experience.- Model fine-tuning experience.- Experience building agent-driven automation where LLM agents take actions.- Background in growth engineering, performance marketing, or data science.- Experience with Mastra or similar agent orchestration framework.What You Will OwnOwn the intelligence and optimization layer of Learn Engine. Build recommendation engines for bid changes, budget reallocation, pause/boost decisions, and postback optimization. Turn SSOT campaign data into high-quality optimization guidance and closed-loop decision systems. Define how the system learns from outcomes and continuously improves campaign strategy over time. This role owns decision quality, optimization policy, and learning loops, not platform plumbing or simulator infrastructure.Pay: $200,000.00 - $1,000,000.00 per yearWork Location: In person

AI Engineer - Learn Engine: Intelligence & Optimization

Vast

<div><h1 class="jobSectionHeader">Developer Experience Engineer</h1>
Vast.ai &middot; Los Angeles or San Francisco Bay Area<h3 class="jobSectionHeader">
About Us</h3>
Vast.ai&rsquo;s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing&mdash;reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
We've never had a dedicated role focused on the developers who build on Vast: the people renting compute from us to train and ship their models. That's what we're hiring for. You'll be our first DevEx Engineer, and you'll own the experience of building on Vast: the reference implementations and example code developers copy, and how we show up in the community around them.<h2 class="jobSectionHeader"> 
Why now</h2>
There's already an active community around Vast in our Discord, on Reddit, on X, and in YouTube comments. Some of it is the builders you'll serve; some of it is hosts and noise. Nobody on our side is really in there today, and our competitors staff this heavily. So part of the job is showing up for the developers who are already here, and part of it is growing the right audience around them. 
 
What you'll own<ul><li>
Technical content. Tutorials, example repos, and short videos that show people how to get something running on Vast. The useful kind that developers pass around on their own.</li><li>
Product feedback. You'll hear what's broken before anyone else does. Get it back to the product team, clearly and often.</li><li>
Events. Run our presence at hackathons (we already have sponsorships lined up), meetups, and conferences, including getting on a plane and showing up in person.</li><li>
Community. Be a real presence in our Discord, on Reddit, and on X. Answer the actual technical questions people ask, the kind they post at 1am when a container won't start. Set the tone for how Vast talks to developers.</li><li>
Creator partnerships. Work with developer-focused YouTubers and other creators, the ones with real audiences rather than bought ones.</li></ul> 
What you won't own
To be straight about scope: this role doesn't cover paid ads, brand and positioning strategy, or the growth dashboard. It's also focused on the demand side, the developers who build on Vast, not our GPU hosts and suppliers, who have their own very different needs. Other people own all of that and you'll partner with them. We want your time going into the builder community and the content that serves it, because that's where it pays off. 
 
Who you are<ul><li>
You've been an engineer. You can deploy a model and debug someone's setup, and developers can tell you've done the work yourself. This part can't be faked.</li><li>
You've built a developer community before, ideally close to from scratch. You know what makes one grow and what quietly kills it.</li><li>
You like people more than most engineers do. Writing, posting, talking, showing up at events. That's the actual day-to-day.</li><li>
You run yourself. Nobody's going to hand you a content calendar, and you'd rather ship something than sit in a planning meeting about it.</li></ul> 
Nice to have<ul><li>
Time at a cloud, GPU, AI-infrastructure, or developer-tools company.</li><li>
Something you've made that traveled: a tutorial series people reference, a repo with real stars, a talk that got passed around.</li><li>
Working knowledge of the AI/ML stack: model deployment, inference, fine-tuning.</li></ul> 
Your first 90 days<ul><li>
Get a steady, regular presence going on Reddit and Discord.</li><li>
Ship your first batch of tutorials and example repos.</li><li>
Represent Vast at a hackathon we're already sponsoring this summer.</li><li>
Give us a clear read on how other GPU and AI-infra companies show up with developers, and where we're behind.</li></ul> 
Compensation and location
$160,000&ndash;$200,000 base depending on experience, plus equity. We're profitable, venture-backed, and growing, so the equity is a stake in a real company with a real valuation, not a lottery ticket. Los Angeles or San Francisco Bay Area. Travel and conference budget covered.<h3 class="jobSectionHeader">
Benefits</h3><ul><li>
Comprehensive health, dental, vision, and life insurance</li><li>
401(k) with company match</li><li>
Meaningful early-stage equity</li><li>
Onsite meals, snacks, and close collaboration with founders/tech leaders</li><li>
Ambitious, fast-paced startup culture where initiative is rewarded</li></ul>
Compensation Range: $160K - $200K</div>

Developer Experience Engineer

Anthropic

<div><div><h2 class="jobSectionHeader">About Anthropic</h2>

Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</div><div><h2 class="jobSectionHeader">
About the role</h2>

The Fraud Prevention team protects Anthropic's payment and monetization surfaces from financial abuse &mdash; keeping fraud losses, dispute rates, and network monitoring exposure in check while preserving a smooth experience for legitimate customers. As a software engineer on this team, you will build the systems that make risk decisions in real time, manage the dispute and chargeback lifecycle, and detect monetization abuse across subscriptions, in-app purchases, and promotions. The ideal candidate can see things from attackers' perspectives, anticipate their responses to countermeasures, and never loses sight of the fact that a false positive here is a paying customer.

Payments fraud is more externally coupled than most trust and safety work &mdash; you'll collaborate closely with finance, support, and legal teams internally, and with payment processors and platform partners externally.
<h2 class="jobSectionHeader">
Responsibilities:</h2>
<ul><li>Design and build real-time risk decisioning that scores transactions at authorization time, balancing fraud loss, approval rates, and latency constraints</li>
<li>Build tooling and automation for the dispute and chargeback lifecycle, from review queues to evidence collection and loss reporting</li>
<li>Engineer fraud signals at scale &mdash; device fingerprinting, BIN and issuer signals, velocity features, and cross-account linkage &mdash; and detect monetization abuse across subscriptions, trials, promotions, and in-app purchases</li>
<li>Own a portfolio of metrics &mdash; loss rate, dispute rate, authorization approval impact, and false-positive rate &mdash; rather than optimizing any single number</li>
<li>Lead investigations into emerging fraud patterns, building multi-layered defenses designed for attacker adaptation rather than point-in-time rules</li>
<li>Work cross-functionally with finance, support, legal, and data science, and with external payment processors and platform partners</li>
</ul><h2 class="jobSectionHeader">Minimum Qualifications:</h2>
<ul><li>Proficiency in Python, SQL, and data analysis tools</li>
<li>Experience building or operating fraud, risk, or abuse detection systems in production</li>
<li>Strong communication skills and ability to explain complex technical tradeoffs to non-technical stakeholders</li>
</ul><h2 class="jobSectionHeader">Preferred Qualifications:</h2>
<ul><li>8+ years of industry software engineering experience, with a focus on payments fraud or risk</li>
<li>Fluency with payments rails: card networks, payment service providers (e.g., Stripe, Adyen), in-app purchase platforms (Apple, Google), refund flows, and the chargeback and dispute lifecycle</li>
<li>Direct experience combating fraud typologies such as card testing, stolen-card monetization, refund and chargeback abuse, subscription and trial abuse, promotional abuse, and friendly fraud</li>
<li>Understanding of fraud loss accounting &mdash; fraud loss vs. dispute fees vs. card network monitoring programs (e.g., VDMP, i VFMP, Mastercard ECP) &mdash; and why chargeback rate thresholds carry existential stakes</li>
<li>Experience building hybrid rules-and-ML risk systems: real-time scoring at authorization plus post-authorization review workflows</li>
<li>Experience at a marketplace or subscription business, or on a processor-side or issuer-side risk team</li>
</ul></div><div><div><div><div>
The annual compensation range for this role is listed below.

For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</div></div>
Annual Salary:
$320,000 - $485,000 USD</div></div><div><h2 class="jobSectionHeader">
Logistics</h2>

Minimum education: Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. 
 
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.
<h2 class="jobSectionHeader">
How we're different</h2>

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
<h2 class="jobSectionHeader">
Come work with us!</h2>

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.</div></div>

Staff+ Software Engineer, Financial Fraud

Collective

<div>
 
 About Collective
 
 
 
 Collective is on a mission to redefine the way businesses-of-one work. Our technology and team of trusted advisors help members achieve financial independence by taking care of everything from business incorporation to accounting, bookkeeping, tax services, and access to a thriving community, all in one integrated platform. We believe in empowering self-employed people to enjoy the same tax savings that big companies get, so they can focus on their passion, not paperwork.
 
 
 Featured in Forbes, Business Insider, Yahoo, Bloomberg, Financial Times, TechCrunch, and more. We are backed by General Catalyst, Sound Ventures (Ashton Kutcher and Guy Oseary), QED Investors, Google&rsquo;s Gradient Ventures, Expa, and other investors who have financed iconic companies like YouTube, Substack, Twitch, Box, Hims, Instacart, and Lyft.
 
 
 
 About The Role
 
 
 
 We&rsquo;re looking for a highly motivated Software Engineer to join our growing engineering team. This is an ideal opportunity for someone 0-2 years out of school who wants to work in a fast-paced, high-growth environment. You&rsquo;ll work on financial products that directly impact self-employed individuals and small businesses across the U.S.
 
 
 As a key contributor on our product engineering team, you&rsquo;ll work closely with experienced engineers, product managers, and designers to build and scale core features of our platform. If you're excited to ship fast, learn constantly, and have real product impact from day one, we would be excited to meet you.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Drive end-to-end implementation of features that directly impact solopreneur financial outcomes, owning them from design to launch.
 </li>
 <li>
 Integrate and leverage AI tools (such as Generative AI and LLMs) to build intuitive, automated user experiences and achieve non-linear scalability.
 </li>
 <li>
 Contribute across the full stack (Python/Django, React/TypeScript) to develop core features and build systems that replace manual financial workflows.
 </li>
 <li>
 Collaborate cross-functionally with Product and Design to translate business requirements into best-in-class product experiences and high-impact solutions.
 </li>
 <li>
 Actively participate in technical discussions, code reviews, and planning sessions to elevate engineering practices and shape the technical foundation as we scale.
 </li>
 <li>
 Learn rapidly from senior engineers, consistently developing your expertise and problem-solving skills in a high-growth environment.
 
 
 </li>
 </ul>
 
 What You'll Bring
 
 
 
 <ul>
 <li>
 0&ndash;2 years of experience with a degree in Computer Engineering or a related field.
 </li>
 <li>
 A product mindset, committed to balancing technical excellence with tangible customer and business impact.
 </li>
 <li>
 Eagerness to explore and apply new technologies, including Generative AI and LLMs, to solve complex challenges and automate financial workflows.
 </li>
 <li>
 A proficiency in a core programming language to have built real projects or contributed to a team, and highly motivated to learn more.
 </li>
 <li>
 Familiarity with modern web technologies, either through internships or academic projects.
 </li>
 <li>
 Based in the Bay Area and are committed to a hybrid schedule (3 days/week onsite in SF).
 </li>
 <li>
 Curious, collaborative, a strong sense of ownership and urgency.
 
 
 </li>
 </ul>
 
 What We Offer
 
 
 
 <ul>
 <li>
 Hybrid Work Model: Based in San Francisco with a balance of in-office and remote flexibility.
 </li>
 <li>
 Fresh Lunch: Provided on in-office days.
 </li>
 <li>
 Commuter Support: $150 monthly reimbursement for transit expenses.
 </li>
 <li>
 Health &amp; Wellness: $200 quarterly reimbursement to support your well-being.
 </li>
 <li>
 Time Off: Flexible PTO plus 14 company holidays.
 </li>
 <li>
 Comprehensive Coverage: 100% medical, dental, and vision for employees; 75% coverage for dependents.
 </li>
 <li>
 Parental Leave: 16 weeks fully paid.
 </li>
 <li>
 Retirement &amp; Ownership: 401k plan plus an equity package.
 </li>
 <li>
 Team Connection: Quarterly virtual events and an annual in-person summit.
 </li>
 </ul>
</div>

Software Engineer (New Grad)

Instabase

<div><div>At Instabase, we're passionate about democratizing access to cutting-edge AI innovation to enable any organization to solve previously unsolvable unstructured data problems in their industry. With customers representing some of the largest and most complex organizations in the world, and investors like Greylock, Andreessen Horowitz, and Index Ventures, our market opportunity is near infinite.

Instabase offers a consumption-based pricing model where customers can pay only for what they use, aligning directly with the value our products deliver. It empowers our clients to explore our AI Hub platform features extensively, enabling them to uncover crucial business insights. This customer-centric model allows Instabase to glean insights from diverse use cases and behaviors, ensuring we deliver top-tier solutions that provide unmatched advantages for everyday business operations.

With offices in San Francisco and Bengaluru, Instabase is a truly global company. We are people-first, and we've built a fearlessly experimental, endlessly curious, customer obsessed team who work together and help organizations around the world turn their unstructured data into insights instantly.</div><h1 class="jobSectionHeader">
Technical Lead Manager (TLM) &mdash; AI Systems &amp; Agents</h1>
<h2 class="jobSectionHeader">About Instabase and the Evolution of Our Business Model</h2>

Instabase is the pioneer in helping the world's largest enterprises&mdash;including global banks, insurance leaders, and healthcare giants&mdash;unlock and automate value from unstructured data. Our core platform is the industry standard for reading, understanding, and processing complex, unstructured documents at massive scale.

As a strategic addition to our current business model, we are building SuperApp, our natively multimodal, stateful AI assistant and autonomous agent platform. SuperApp represents the next evolution of Instabase: moving from passive document extraction to active, self-correcting agentic execution. By combining our enterprise-grade document understanding with secure, real-time sandboxed code execution, SuperApp enables users to not only parse unstructured data but programmatically act on it, write and run execution scripts, orchestrate complex software tools over Model Context Protocol (MCP), and complete open-ended reasoning tasks in a secure environment.

To lead the engineering team behind this next-generation capability, we are seeking an elite, hands-on Technical Lead Manager (TLM) &mdash; AI Systems &amp; Agents.
<h2 class="jobSectionHeader">
The Role: Player-Coach Leadership</h2>

This is an high-impact, low-bureaucracy role designed for a world-class systems engineer and builder. We keep our teams intentionally lean and fast. You will serve as a Player-Coach leading a tight, elite squad of 3 to 5 AI systems engineers.

At Instabase, we believe managers of small teams should stay close to the metal. Your time will be split:
<ul>
<li>60% to 70% Hands-on Engineering: Actively designing multi-turn agent loops, writing production code, building secure sandboxing environments, and architecting systems.</li>
<li>30% to 40% Leadership &amp; Mentorship: Recruiting top-tier talent, mentoring engineers, reviewing PRs, and aligning product roadmaps with technical execution.</li>
</ul><h2 class="jobSectionHeader">What You Will Do</h2>
<ul><li>Architect Stateful Agent Loops: Design and implement highly reliable, multi-turn agentic planning and execution state machines capable of self-correction, tool orchestration, and long-context memory persistence.</li>
<li>Build Secure Execution Sandboxes: Own the runtime execution layer where model-generated code (such as Python data-analysis scripts) is safely isolated, monitored, and run in real-time without compromising enterprise security boundaries.</li>
<li>Pioneer Tool Orchestration &amp; MCP: Expand our agent capabilities by designing composable tool-calling integrations using Model Context Protocol (MCP) and custom API interfaces.</li>
<li>Build Evaluation &amp; Trajectory Testing Harnesses: Establish programmatic frameworks (using LLM-as-a-judge and trajectory evaluations) to test if agent loops, tool-calling selections, and error recoveries behave safely and deterministically.</li>
<li>Scale High-Performance Systems: Work on deep systems problems including latency optimization, semantic caching, speculative execution, and streaming intermediate agent states for a responsive user experience.</li>
<li>Scale the Team: Bootstrap, hire, and mentor a small, elite, high-velocity team of software and AI engineers.</li>
</ul><h2 class="jobSectionHeader">Our Technical Stack</h2>
<ul><li>Orchestration &amp; Frameworks: LangGraph, LangChain, Go/Python, React, Node, Next.js.</li>
<li>Infrastructure &amp; Security: Secure sandboxed runtimes (Docker, gVisor, WebAssembly), GCP, AWS, Kubernetes, Cloud SQL (PostgreSQL, TimescaleDB), Redis, Pub/Sub.</li>
<li>AI &amp; Models: Integration with advanced reasoning models (GPT-4o, o3, Claude 3.5 Sonnet, DeepSeek) across custom function-calling, LLM fine-tuning, and hybrid vector-search RAG pipelines.</li>
<li>Standards: Model Context Protocol (MCP) tool schemas and APIs.</li>
</ul><h2 class="jobSectionHeader">About You</h2>
<ul><li>8+ Years of Professional Engineering Experience: A strong, proven background in software engineering, with significant tenure building and scaling backend systems, infrastructure, or platform services.</li>
<li>Active LLM &amp; Agentic Engineering Experience: Practical, hands-on experience building production-grade LLM applications, multi-agent workflows (using DAGs or state machines), or tool-calling executors.</li>
<li>Systems &amp; Infrastructure Rigor: Deep familiarity with building secure sandboxed runtimes, container isolation, API platforms, caching strategies, or high-throughput real-time data streaming.</li>
<li>Small-Team Leadership Experience: Proven track record of mentoring senior engineers, driving technical design reviews, and leading high-velocity squads as a Tech Lead, TLM, or hands-on EM.</li>
<li>An Active Builder: You love writing code. You are excited about the prospect of coding daily and staying out of the meetings and administrative bloat of traditional big-tech management.</li>
<li>Educational Background: BS, MS, or Ph.D. in Computer Science, Computer Engineering, or a highly quantitative field.</li>
</ul>
Compensation: The base salary range for this role is $230,00 to $270,000 + bonus, equity, and benefits. The actual pay may vary based on factors such as location, experience, and skills.
<div>
<div>US Benefits:</div>
<ul><li>Flexible PTO: Because life is better when you actually live it!</li>
<li>Comprehensive Coverage: Top-notch medical, dental, and vision insurance.</li>
<li>401(k) with Matching: We've got your back for a secure future.</li>
<li>Parental Leave &amp; Fertility Benefits: Supporting you in growing your family, your way.</li>
<li>Therapy Sessions Covered: Mental health matters&mdash; 10 free sessions through Samata Health.</li>
<li>Wellness Stipend: For gym memberships, fitness tech, or whatever keeps you thriving.</li>
<li>Lunch on Us: Enjoy a lunch credit when you're in the office.</li>
</ul>
#Li-Hybrid</div><div> 

</div><div>Instabase is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. Research shows that in order to apply for a job, women feel they need to meet 100% of the criteria while men usually apply after meeting about 60%. Regardless of how you identify, if you believe you can do the job and are a good match, we encourage you to apply.</div></div>

Technical Lead Manager

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