Define end-to-end requirements for AI capabilities, from model behavior to user experience.
Translate model capabilities and technical constraints into product decisions.
Work closely with ML and engineering teams on system design and iteration.
They develop AI-powered email applications and work at the intersection of user needs and model capability. The company is fast-moving and collaborative with a strong focus on technical ownership and innovation.
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.
Own the strategy, roadmap, and execution for specialized AI agents and evaluation infrastructure.
Ship large, technically complex agent capabilities end-to-end with a high degree of autonomy.
Define agentic development standards, mentor junior PMs, and build cross-functional partnerships.
Smartsheet empowers teams to manage work seamlessly and scale solutions, and is now uniting human teams with AI agents to automate tasks and uncover insights. With over 20 years of experience, the company fosters a culture of innovation, collaboration, and personal growth.
Own agent definition, problem selection, and the human-in-the-loop contract.
Work hands-on with AI Lab engineers and the CEO to prototype, evaluate, and ship WFM agents.
Own build quality, evaluation, FRDs, commercialization, and design-partner delivery.
Legion Technologies provides an AI-driven workforce management platform that maximizes labor efficiency and employee engagement for hourly workers. It is a remote, mission-driven company with a collaborative, fast-paced culture.
Lead the engineering strategy and execution for evaluations of AI agents, owning the core evaluation platform.
Design scalable evaluation infrastructure, APIs, workflows, and production systems across software categories.
Mentor and develop a team of engineers as the technical authority on agentic evaluation.
This company focuses on building credible, scalable evaluations of AI agents from software vendors. It operates as a fully remote, inclusive team with a flexible culture and a focus on professional growth.
Own the build out of new agents, skills, and platform capability for teams across TLDR.
Build and deploy agents end to end, from design through implementation, evals, and rollout to internal users.
Partner with stakeholders across sales, editorial, and people ops to find where an LLM belongs in their process.
TLDR runs the largest network of tech newsletters in the world, with over 8 million subscribers covering startups, software engineering, AI, and more. Our 31-person full-time team is bootstrapped, profitable, and on track for $35M in revenue this year, with a culture of owning functions rather than slices.
Design AI evaluations: define ground truth, metrics, and scoring methods for models and agents.
Build repeatable eval loops to track quality over time and catch regressions before release.
Translate eval results into actionable recommendations for system improvements.
Alpaca is a global leader in agent-first brokerage infrastructure, providing APIs for stocks, ETFs, options, crypto, and more. We're a diverse team of 400+ remote-first members backed by $400M in funding, committed to opening financial services to everyone.
Represent the customer: develop deep understanding of creative and marketing workflows through frequent customer engagement and synthesize findings on agent performance.
Lead Agent Development: run user interviews, competitive research, eval analysis, and prompt experimentation to shape new product offerings.
Own agent quality: create eval infrastructure, monitor regressions, and ensure agents improve with every release.
Runway builds AI to simulate the world, merging art and science through its all-in-one platform for generating and editing video, images, and audio. The company has a creative, ambitious team and has been recognized as a best place to work.
Set the technical direction for AI engineering across the team: agent architecture patterns, evaluation methodology, deployment and monitoring strategies
Design the AI platform layer, including shared agent frameworks, tool integrations, and evaluation infrastructure
Work directly with clients on the most complex engagements, identifying new problem domains and ensuring 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 managing nearly $10 trillion in assets, Addepar fosters a culture of ownership, collaboration, and innovation.
Own agent quality end-to-end for Bliro's chat and voice agents, including prompting, context, and model evaluation.
Build eval sets, LLM judges, and benchmarks to measure quality, latency, and cost with statistical rigor.
Establish a repeatable process for improving agent quality and set the long-term technology roadmap.
Bliro builds an AI assistant that handles desk work for field sales teams, with over one million customer touchpoints documented. Backed by leading investors and trusted by German Mittelstand companies, it's a small, high-performing team that values ownership and continuous improvement.
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.
Own one AI agent end to end: discovery, first implementations, and roadmap.
Spend significant time on-site with credit union executives shaping products and driving go-lives.
Collaborate with AI PMs and commercial counterparts to decide where agents launch and scale.
Clutch is a vertical SaaS company building AI agents for credit unions, helping them become fintech lenders. It is a small, senior team backed by Andreessen Horowitz with a high-ownership, low-process, and AI-forward culture.
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.
Build RL environments, agentic systems, LLM pipelines, and evaluation frameworks for real-world AI use cases.
Develop benchmarks and evaluation harnesses to assess model quality across accuracy, safety, latency, and cost.
Conduct fine-tuning and model experiments, deploy self-hosted models, and document reproducible methodologies.
The employer is an organization focused on applied AI research, building practical and reusable AI systems for real-world use cases. It values curiosity, accountability, innovation, collaboration, and continuous learning in a remote environment.
Own your platform end to end, shaping strategy and roadmap from requirements through launch and adoption.
Define and measure success with technical requirements, metrics, and AI-powered improvements.
Partner across data, product, and business teams to balance long-term bets with near-term wins.
Engine is an AI-native platform for intelligent travel, powering business travel for over 40,000 customers and nearly 2 million travelers. The company has an ambitious, fast-paced culture recognized as a best place to work, with high-caliber colleagues and full ownership.
Design and implement autonomous agents and multi-agent orchestration systems for complex, open-ended tasks.\n- Build and optimize production-grade LLM applications with a focus on reliability, observability, and low-latency performance.\n- Architect advanced RAG pipelines and vector database strategies to provide agents with accurate, real-time context.
Jobgether is an AI-powered job matching platform that connects candidates with hiring companies through objective evaluation. The company operates with a distributed, global-first team culture, emphasizing fairness and innovation in recruitment.
Evaluate AI model responses across diverse topics and use cases against established quality standards.
Write, test, and refine system prompts to influence model behavior and performance.
Identify and document model failures and provide clear, actionable feedback to product teams.
This company specializes in evaluating and improving advanced AI systems through content evaluation and prompt engineering. It operates as a partner company managing applications for this role, focusing on quality and consistency in AI behavior.
Develop and deploy cutting-edge AI/ML solutions to enhance the platform and improve student learning experiences.
Design, develop, and optimize LLM-powered agentic systems and APIs for real product use cases.
Collaborate with senior engineers and contribute to evaluation frameworks and MLOps pipelines.
Interview Kickstart specializes in interview preparation and career transitions into high-demand tech fields like AI, ML, and Data Science. Over 17,000 tech professionals have been guided by current and former hiring managers to land coveted positions at companies like Google and Amazon.
Test and evaluate AI model responses across diverse topics and conversation types.
Write and refine system prompts to shape model behavior and personality.
Apply detailed rubrics consistently to assess model performance and document findings.
We are a team dedicated to evaluating and improving advanced AI models and products. Our fast-moving environment emphasizes quality, independent judgment, and attention to detail.
Design, build, and deploy LLM-powered product features, including lab summaries and conversational agents.
Build backend services integrating LLMs and ML models, primarily using Python with exposure to Elixir.
Implement evaluation, monitoring, and CI/CD workflows for AI features, ensuring reliability and clinical relevance.
Fullscript is a health technology platform that helps practitioners deliver better care through clinical insights, lab interpretations, and patient analytics. With over 125,000 practitioners and 10 million patients, the company emphasizes a people-first culture, teamwork, and continuous learning in a remote-first environment.