Founding AI Engineer
Location
California
Posted
6 days ago
Salary
$170K - $250K / year
Seniority
Senior
No structured requirement data.
Job Description
Founding AI Engineer
kos.ai
Title: Founding AI Engineer Location: San Francisco Department: Engineering Job Description: About kos.ai Trillions of dollars are flowing into datacenters, defense, energy, and manufacturing. The finance teams processing that capital can't keep up. 800-page invoices, thousand-page contracts, landing every few weeks, often on weekends. The world can't hire specialized accountants fast enough. Media: The Information covering our launch The Role You'll own the agent loop, the model orchestration, and the eval infrastructure. Kos is processing billions of dollars of customer work. Your systems are what keep that right. You'll own how that system gets built and how it gets better. Your work lands in production at some of the largest and fastest-growing infrastructure and defense companies in America. What you'll do: - Own the agent runtime: computer use, tool orchestration, and memory loop that lets Kos learn a workflow from customer demos - Design the ensemble routing layer that picks the right model per step and keeps Kos.ai provider-agnostic - Build the evaluation harness that catches regressions on recorded customer workflows before they reach production - Take frontier agent capabilities from paper to production, with equal attention to what the research says and what runs reliably every day - Partner with the applied controller team so practitioner-caught errors turn into prompt, model, and routing improvements - Set the hiring bar and culture for Kos.ai You - Have strong fundamentals: Bachelors / Masters / PhD in CS/EE from top-tier universities, 2+ years of experience - Have shipped an agentic system, computer-use agent, or LLM-powered feature into production. Or you have an equivalent research track record. - Worked on modern LLM orchestration, tool use, eval design for open-ended tasks, and the tradeoffs between fine-tuning, prompting, and retrieval are second nature to you - Can take a problem from "interesting paper" to "runs reliably every day for paying customers" without being told how to scope it - Track agent and LLM research closely. Useful ideas turn into production experiments in your hands quickly. - Care as much about the eval harness as the model weights. Benefits - Medical, dental, vision for you and your dependents (little/no premiums, the absolute best we qualify for) - 401(k) - Visa sponsorship Team Tanuj and Mani met at Stanford as graduate researchers under Sachin Katti. Tanuj spent his career in and around the operators Kos serves: IT, datacenters, industrials, and hardware. He previously founded Spot AI, a computer vision company which scaled to over 1,000 enterprise customers. Mani's an International Olympiad medalist, earned his Engineering PhD at Stanford, & published leading research at Microsoft Research. He then built product within Microsoft Azure's Strategic Missions and Technologies group. We built Kos because the finance and operations teams behind America's re-industrialization are talented, overwhelmed, and can't hire their way out. Every CFO we spoke to described the same problem: 800-page pay apps, thousand-page contracts, work piling up on weekends, and a talent pool for inventory, utilities, capex, and construction accounting that's simply too small to meet the moment. The back office of the buildout is the bottleneck, and it's the one nobody's building for. They deserve a partner that can keep pace with their ambition.
Related Guides
Related Job Pages
More AI Engineer Jobs
• Join a team that is passionate about helping each other • Work on AI solutions for logistics operations
AI Platform Administrator
CloudScoutsA group of passionate technologists and EPM process specialists...
• Manages AI platforms and environments, including access provisioning, governance controls, and policy enforcement (e.g., DLP, security, and compliance) • Develops reusable components (e.g., prompts, connectors, APIs, templates) to accelerate AI solution delivery and promote standardization across use cases • Designs and maintains the foundational AI infrastructure, frameworks, and observability capabilities (telemetry, monitoring, metrics) required for scalable, reliable, and governed AI operations • Enforces security protocols, data handling rules, and role-based access controls in collaboration with InfoSec and Legal • Oversees workspace configuration, user provisioning, single sign-on (SSO), and licensing • Connects AI tools with core enterprise software (like HRIS, CRMs, and document repositories) • Creates internal training materials, troubleshooting guides, and tracks AI usage metrics to drive value realization • Tracks platform performance, API error rates, and token consumption to optimize operational costs
• Architect and implement production-ready AI solutions involving LLMs, transformer-based models, retrieval systems, agentic workflows, and AI agents for generative tasks and automation. • Design and iterate on prompts, workflows, and RAG pipelines to improve accuracy, cost-efficiency, latency, and safety. • Design and build multi-step agentic systems that break down complex tasks, invoke external tools or APIs, manage state, and handle reasoning chains robustly. • Deploy models and GenAI pipelines in production environments (API, batch, streaming), ensuring reliability and scalability. • Build and maintain evaluation frameworks to measure model grounding, factuality, latency, and cost. • Develop and integrate guardrails (e.g., prompt-injection protections, content moderation, output validation), and safeguards for agent loops (e.g., loop prevention, tool call limits, state validation). • Collaborate cross-functionally with Product, Engineering, and ML Ops to deliver high-quality AI features end-to-end.
• We are building the newsroom of the future in Germany’s largest financial portal. • AI handles routine tasks so our editorial team can focus on what truly matters: context, analysis, and point of view. • AI-driven workflows for market reports, earnings recaps, economic updates, and much more • Development of multiple n8n flows as a central editorial asset • Wide selection of tools, API integration, quality assurance – end-to-end content repurposing at scale: articles, newsletters, and social media.



