Founding Forward Deployed Research Engineer (FDRE)

Poolside
Forward Deployed EngineersPosted 24 February 2026

Job Description

ABOUT POOLSIDEIn this decade, the world will create Artificial General Intelligence. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will define the winners. These companies will move faster than anyone else. They will attract the world's most capable talent. They will be on the forefront of applied research, engineering, infrastructure and deployment at scale. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this. They will create powerful economic engines. They will obsess over the success of their users and customers.Poolside exists to be this company: to build a world where AI will be the engine behind economically valuable work and scientific progress. We believe the fastest way to reach AGI lies in accelerating software development itself, by reshaping the developer experience with agentic systems, coding assistants, and the frontier models that power them. We deploy these systems directly into the development environments of security-conscious enterprises.ABOUT OUR TEAMYou’ll join a tight-knit group of engineers and researchers from leading labs and product companies (DeepMind, Palantir, GitHub, among others). The culture is low-ego and high-bar, organized around hard problems. It’s a place to learn by building - side-by-side with people who care about craft, rigor, and impact - on challenges that matter and aren’t found anywhere else. Very few companies get a seat at this table, and all the ingredients are in place to give us the right to win. Now we just need to execute.ABOUT THE ROLEAs an FDRE, you'll be embedded with customers, figuring out how to build real agentic systems to solve hard problems.Hard problems aren’t solved from an armchair; the right to solve them comes from experience, resilience, and a little scar tissue, earned by engaging with reality.This role gives you direct exposure to frontier AI R&D and a front-row seat to the most valuable problems and industries on the planet. You’ll operate at the intersection of software engineering, applied AI and agent research, and product - designing and deploying high-reliability systems, while feeding signal back into our products and models.RESPONSIBILITIESFDREs work in small teams with the agility and autonomy of a startup, but with the experience and support of an established organization. Among other things, you willOwn the mission end-to-end. Be the technical owner in the field, clarify goals, shape the plan, make the hard calls, and ship systems that move real metrics.Partner for impact. Work directly with operators and executives to scope what matters most, then turn it into production results.Build with research in the loop. Collaborate with AI R&D on prompts, tools, and model improvements; bring back field-signals that make the next model, and the platform, better.Turn wins into a flywheel. Convert patterns into playbooks, products, and libraries so that every deployment is faster, more powerful, and more reliable than the last.WHAT YOU'LL SEE IN THE FIELDThese are the kinds of skills and technologies you’ll likely use and develop over time. Strong experience in any is a plus, not a prerequisite. We look for spikes!Software engineering & platforms: Backend services at scale; distributed systems; data/feature pipelines; queues/caching; fault tolerance.Agentic/LLM systems: multi-agent systems; agent communication/delegation; evals; long-running, fault-tolerant agents; tools/prompt/program design; guardrails.Evaluation & experimentation: Designing evals; monitoring performance/drift; fundamentals of Data Science/ML; able to turn a hazy problem into a structured exploration.Cloud & ops: Kubernetes, Docker, IaC (Terraform/CDK), networking, secrets, observability (Grafana/Prometheus/Datadog), CI/CD.Model ops: Fine-tuning/RL; designing agent environments; managing inferenc ... (truncated, view full listing at source)
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