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.
Architect and implement production-ready generative AI and LLM-based solutions within the product suite
Design and develop agentic systems, RAG pipelines, and evaluation workflows to automate tasks and improve reliability
Collaborate with product, design, and engineering teams to turn complex AI concepts into user-facing features
JUPUS is a fast-growing legal tech company in Europe, building the JUPUS platform to improve productivity for law firms. The culture is flat, fully remote, and fast-moving, with direct access to engineering leadership and a focus on practical AI systems.
Build and ship production AI systems for the core finance workflows.
Own evals: metrics, test datasets, and monitoring of quality, cost, and latency.
Iterate end-to-end on AI products, from data pipelines to deployment.
Sibill is an AI-powered platform that unifies invoicing, payments, treasury, and accounting for SMEs and accountants in Italy. Backed by €12M from Creandum, the company serves over 5,000 businesses and 300+ firms with a team of over 130 people.
Own product features end-to-end, from problem statement to production.
Write specs with AI agents and critically review their code in complex systems.
Deliver reliable features handling financial transactions and evolve AI-first development.
Social Discovery Group creates social entertainment platforms that connect people online across cultures, addressing loneliness and disconnection. The company's international remote team works from everywhere, and it earned 'Great Place to Work' recognition in 2024-2025.
Guide architectural decisions across products, reviewing solutions from internal teams and vendors.
Establish shared engineering standards and modernise legacy systems for reliability and cost-effectiveness.
Define guardrails for production LLM systems and collaborate with teams on Kubernetes and cloud infrastructure.
INFUSE is a technology company that develops software products, including AI and LLM-based solutions, across a large engineering landscape. Its software department spans 500+ repositories and fosters a remote-first culture with access to cutting-edge AI tools and human-centric values.
Act as the technical bridge between enterprise customers and core engineering, designing APIs, SDKs, and workflows.
Architect production-ready AI infrastructure for LLM inference, RAG pipelines, and GPU-accelerated workloads.
Write production-grade Go, Python, and TypeScript while shaping product strategy and mentoring engineers.
The hiring partner builds modern developer platforms and AI infrastructure that help enterprises ship AI-native applications. The team culture emphasizes hands-on technical excellence and collaboration; company size is not disclosed in the posting.
Design and build the gateway, runtime, and evals services for AI workloads at scale.
Own technical decisions from design to launch, including identity, quota, and failover controls.
Partner with security and infrastructure teams to set guardrails for agentic workloads.
We provide clear, predictable pay-over-time financial products with no hidden fees. We are a remote-first company with an engineering culture centered on blameless postmortems and detailed technical design.
Own AI workflows end to end, from problem definition to production and improvement, for finance processes like invoice-to-payment and reconciliation.
Design and build production-grade LLM-based systems with structured outputs, RAG, validation, and monitoring.
Collaborate with product, backend engineering, and customers while setting technical direction and using AI coding tools daily.
Jeeves is a stablecoin-native banking platform providing corporate cards, payments, treasury, and spend management for global enterprises. With over $5B in annualized volume and backing from top investors, the company is scaling rapidly and values relentlessness and tackling hard problems.
Prototype AI applications quickly to explore new opportunities in data and marketing workflows.
Work with a small team to develop and ship product ideas, laying the groundwork for new capabilities.
Build production data agents that use company data to answer analytics and data science questions.
The company is a Series D marketing technology firm building AI-powered tools for data and marketing workflows. It operates with a high-velocity product culture, typical of growth-stage startups, and values quick prototyping and production-grade engineering.
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.
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 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.
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 build automated evaluation pipelines for AI agents.
Develop testing frameworks for reasoning, multi-turn conversations, and adversarial scenarios.
Own the evaluation architecture and integrate observability tools in a fully remote team.
A company building production-grade AI agents and systems. They operate in a fully remote, globally distributed environment with a culture focused on innovation, autonomy, and continuous improvement.
Own end-to-end delivery of agentic platform features, from design to production.
Architect and scale the runtime that powers AI agents across the company.
Mentor engineers and drive reliability, cost, and security in production.
Alan is a health insurance and prevention platform that integrates insurance, prevention, and care into a single user experience. With over 1,000 employees, 1M+ members, and 40K+ partner companies, the company fosters a culture of ownership, speed, and collaboration.
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.
Prototype and evaluate AI applications for data and marketing workflows.
Develop production data agents and backend services with Node.js and TypeScript.
Design AI-assisted experiences and choose AI architectures for real user workflows.
The company builds AI capabilities for B2B marketing and data workflows, helping users turn customer data into useful insights and actions. It operates like a small, high-velocity startup team focused on shipping production-ready AI products.
Lead a small engineering team as a hands-on player-coach, setting technical direction and owning delivery.
Ship AI-powered features to production while raising standards across observability, testing, security, and architecture.
Partner with Product and leadership to plan, prioritize, and follow through on complex technical work.
Usersnap is building AI-driven capabilities into its product, from automated setup to intelligent surveys and reporting. It is part of saas.group, a remote portfolio of 380+ SaaS professionals across 50+ countries, with a high-trust, flexible culture.