Transform an existing AI agent product into scalable, reliable infrastructure.
Design and operate the core agent runtime, including orchestration, memory, and multi-agent workflows.
Work directly with the founder to set architecture, engineering standards, and development culture.
An early-stage AI infrastructure startup transforming a working AI agent product into scalable infrastructure. As the first engineering hire, you'll work directly with the founder to shape engineering culture and standards from the ground up.
Design and deploy AI agents that automate sales, operations, and support workflows.
Own technical delivery end-to-end, from architecture to production and post-launch improvements.
Work directly with clients to understand workflows and explain technical tradeoffs.
Stello is an AI transformation firm that partners with mid-market and enterprise companies to automate repetitive work with AI agents. They work across sales, operations, and customer support, deploying solutions inside existing client tools.
Define end-to-end requirements for AI capabilities, from model behavior to user experience.
Translate model evaluations and technical constraints into clear product and system decisions.
Own product quality end-to-end, ensuring AI systems are reliable, predictable, and trusted.
The company is building AI-powered email applications, leveraging machine learning and large language models to enhance user experience. It is a fast-moving, zero-to-one environment where engineers and product teams collaborate closely with significant ownership.
Prototype and test ideas for applying AI to data and marketing workflows.
Develop and ship production-ready AI applications in close collaboration with product and engineering teammates.
Make architectural and framework decisions for LLM-based systems and build data agents that answer analytics questions.
This is a Series D marketing technology company focused on building AI experiences that help teams use data to improve marketing workflows. They are a small, fast-paced product and engineering team within a venture-backed startup environment.
Build repeatable benchmarks and evaluation pipelines for model accuracy, hallucinations, retrieval quality, latency, and cost.
Turn research prototypes into production retrieval, drafting, document, and agent workflows.
Develop backend services, APIs, and internal tools to support testing and releases.
They are a healthtech company building dependable AI products for legal work. Their team is product-focused and works remotely across the United States.
Build AI-powered agents and tools end-to-end: identify problems with clients, prototype quickly, evaluate rigorously, and ship to production.
Design and implement LLM integrations including prompt engineering, function calling, structured outputs, and retrieval-augmented workflows.
Work directly with clients to understand workflows, validate AI behavior, and iterate toward production quality.
Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. With over 1,500 firms in 60 countries and nearly $10 trillion in assets on the platform, Addepar fosters a culture of ownership, collaboration, and continuous learning.
Own AI agents and autonomous workflows powered by LLMs from problem framing through production.
Build RAG pipelines, set evaluation and guardrail standards, and optimize for cost and scalability.
Work directly with client teams to scope problems and deploy AI systems in their environments.
Acceler is a Forward-Deployed Engineer company that takes AI from pilot to production inside client systems. With a practitioner network of nearly 1,000 engineers across the US and India, it's a high-caliber team built on ownership, trust, and rapid learning.
Build and ship LLM-powered applications and AI agent workflows.
Design systems for reasoning, planning, memory, tool use, and multi-step execution.
Optimize AI systems for quality, latency, and cost, and establish production practices for observability and evaluation.
Gina's Tech Jobs is a technology recruiting firm that connects companies with engineering and IT professionals. They focus on remote and onsite placements, offering personalized recruitment services and career support.
Build and improve AI agents by writing production code for Voice Agent and Autopilot platforms.
Own enterprise AI deployments from initial discovery through go-live, working directly with customers.
Design and implement AI workflows, debug agents in production, and turn customer needs into reusable product features.
Supermove builds software and AI for moving companies, providing systems for sales, operations, crews, and billing. The company has raised $30M from investors like Andreessen Horowitz and serves moving businesses across the US, Canada, and Australia.
North America
Unlimited PTO
18w maternity
12w paternity
Own vision, strategy, and roadmap for Source's agent platform, including framework, sessions, memory, and evals.
Set the quality bar for non-deterministic AI products by defining evals, guardrails, and success metrics.
Build reusable primitives and MCP/CLI interfaces for marketing teams and developers to extend Source.
Webflow is the agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize web experiences. They are a growing, privately held company focused on craft, quality, and inclusivity.
Design and deliver production-grade agents that investigate, reason, and act on live observability data.
Own agent work from rough prototype to production, including evals.
Extend the agentic workspace with new canvas capabilities, MCP server, and skills.
Honeycomb provides an observability platform that helps engineers understand and debug complex systems. It is a fully distributed company of over 200 people, with a culture that values impact, autonomy, and inclusivity.
Build and deploy AI workflows and skills using AIVA
Integrate AI solutions with APIs, databases and enterprise systems
Rapidly build, test, demonstrate and refine solutions with clients
Williams Lea is the leading global provider of tech-enabled business and marketing services helping clients manage and transform processes. The company serves clients in 20 countries across four continents and has 15,000 employees worldwide.
Develop the architecture and infrastructure needed to scale the product to a large user base.
Build and operate the agent runtime, including orchestration, memory, verification, and supporting systems.
Take projects end to end across backend, infrastructure, frontend, and AI agents.
They are an early-stage AI infrastructure startup building scalable infrastructure for AI-powered service businesses. As the first engineer, you'll work directly with the founder in a fast-moving, ownership-driven culture.
Rebuild the existing product into infrastructure designed to support significant growth.
Design and operate agent systems, including orchestration, memory, and verification.
Own projects end to end across backend, infrastructure, frontend, and AI agents.
Early-stage AI company building reliable infrastructure for AI-powered service businesses. It is an early-stage startup at the first-engineer stage, so you'll work directly with the founder to shape architecture and engineering culture.
Build AI features inside real clinical workflows, like checking notes against payer and compliance requirements before finalization.
Design evals to prove those features are right and keep them honest as models change.
Prototype AI capabilities, including voice agents, and take the best from prototype to production.
Ease builds the AI-native operating system for behavioral health, replacing disconnected tools with one platform for CRM, EHR, and revenue cycle management. Backed by a $41M Series A, this rapidly growing NYC team has no product managers—engineers talk to customers and ship in days.
Set technical direction for production agent systems, including orchestration, tool use, memory management, and failure recovery.
Build and operate shared foundations: evaluation frameworks, observability, execution controls, and model access with routing and failover.
Work with security and platform teams to ensure scoped permissions, data isolation, audit trails, and safe execution of tools and code.
Cobalt runs AI agents in production that test real customer applications, operating at the forefront of the pentesting industry. The company is rapidly expanding, offering a collaborative culture with mentorship, competitive compensation, and a focus on growth.
Build evaluations to measure and improve AI reasoning in complex, high-stakes decisions.
Collaborate with engineers, product, and domain experts to turn observed failures into testable improvements.
Own the quality of shipped systems, from code reviews to monitoring and integration.
Elicit builds AI systems that help research and business teams make evidence-based decisions on high-stakes questions. They are a remote-friendly, collaborative team that values rigorous thinking, experimentation, and in-person retreats.
Build tools for understanding traces, evaluating agent behavior, and turning results into improvements.
Run experiments on Mastra's primitives to find where they fall short and improve configuration and behavior.
Help turn findings into capabilities developers can use in their own applications.
Mastra is the open-source TypeScript framework for building AI agents. We're a small, fully remote team backed by Y Combinator and Spark Capital with $35M raised.
Design agent architectures for planning, reasoning, tool use, and memory integration.
Improve reliability on long-running tasks with failure recovery and evaluation systems.
Build loops for agents to improve with real use, balancing quality, latency, and cost.
Adaption builds AI systems that evolve in real-time, making them flexible and personalized. They are a global-first team focused on talent density and collaboration.