2,916 Founding Engineer jobs
Founding engineer roles building the first product at early-stage startups.
IT Engineer
IT Engineer at Watershed owning internal IT systems and SaaS platforms (Okta, Kolide, Iru/Kandji, Google Workspace, Notion, Slack) for a global team — managing the macOS fleet, employee lifecycle provisioning, asset management, automations, A/V, and administering AI tools like Claude and ChatGPT. Based in the San Francisco office, working on-site 4 days per week.
Staff Software Engineer, Product
Staff software engineer on Decagon's Product Engineering team building the conversational AI platform customers use to configure, train, test, and monitor AI agents — self-serve tooling, config abstractions, monitoring/tracing, and model evals, primarily in Python across the full stack, in-office in San Francisco.
Founding Engineer
Founding full-stack engineer building frontend and backend for Jinba's AI-native enterprise workflow automation ('vibe coding') platform. Day to day: system design, data modeling, integrating AI models and natural-language-to-action pipelines. Core stack: TypeScript, React, Vercel/Cloudflare Workers, Terraform, and AI frameworks like Vercel AI SDK and Mastra.
Member of Technical Staff - Pre-Training Infra
Builds and scales the distributed training infrastructure behind Reflection's frontier open-model pre-training: designing large training runs with researchers, optimizing GPU utilization, communication, and memory across thousands of GPUs, and debugging bottlenecks in the distributed training stack using frameworks like Megatron/DeepSpeed and NCCL.
Member of Technical Staff - Compute Platform
Builds and maintains Reflection's Kubernetes-based compute platform for AI model training across multiple cloud providers — handling cluster management, topology-aware GPU scheduling, node health, monitoring, and petabyte-scale storage. Requires deep systems engineering and GPU infrastructure experience (e.g., NCCL).
Member of Technical Staff - Platform Foundations
Platform/infrastructure engineer at Reflection, an open-weight AI research lab, building the company-wide foundations platform in London: golden paths for cloud and networking, security guardrails, CI/CD and build systems, observability, and cloud cost optimization using GCP/AWS, Kubernetes, Terraform/Pulumi, and Bazel.
Member of Technical Staff - Shared Services
Builds and operates the shared-services foundations platform powering Reflection's open AI model research and production environments — developer infrastructure, SRE reliability, and data/compute tooling. Day-to-day work spans Kubernetes container platforms, distributed systems, and services in Go, Rust, C++, and gRPC.
Member of Technical Staff - Applications
Full-stack engineer at AI research lab Reflection, building internal and customer-facing product surfaces (dashboards, admin tools, self-serve workflows) on top of the company platform. Day-to-day spans React/TypeScript UIs, FastAPI/Go APIs, OIDC auth and RBAC, event-driven integrations, and observability tooling.
Member of Technical Staff - Data Ingestion Engineer
Data Ingestion Engineer at Reflection, an AI research lab building open frontier models, builds and operates large-scale data ingestion systems (web crawling, extraction, normalization, versioning, delivery) that turn the open web into training corpora for pre-training pipelines, using tools like Ray, Beam, and Spark.
Member of Technical Staff - Safety
AI Safety engineer at Reflection's London lab who owns red-teaming and adversarial evaluation of the company's open LLMs, builds automated safety benchmarks, researches jailbreaks and defenses, and acts as gatekeeper ensuring model releases meet risk thresholds. Core tech: LLM safety, adversarial eval pipelines, ML systems, RLHF/RLAIF.
Member of Technical Staff - Data Quality Engineer (Pre-training)
Data Quality Engineer on Reflection's pre-training data team at an AI research lab building open foundation models. Day to day: define measurable data-quality standards, build automated QA pipelines, and monitor training data quality for LLM pre-training, primarily using Python and ML/LLM-based evaluation methods.
Member of Technical Staff - Data Quality Engineer (Post-training)
At Reflection, an AI research lab building open models, this London-based engineer owns upstream data quality for LLM post-training: analyzing expert datasets, turning 'good data' into measurable standards, and building automated QA pipelines (including LLM-as-a-Judge) that feed model training and evaluation. Core stack: Python, ML/LLM workflows, and large-scale data systems.
Member of Technical Staff - Evaluations
At Reflection, an AI research lab building open foundational models, you'll design and run LLM evaluations — building benchmarks, human preference and agentic evals, and feedback loops that connect data, evals, and model behavior to drive model improvements across pre-training, post-training, and applied teams.
Member of Technical Staff - Pre-Training
Research engineer role on the pre-training team at Reflection, an AI lab building open foundation models. Day to day you run experiments on scaling laws, data processing, optimizers and model architecture, implement SOTA deep learning methods, and optimize large-scale distributed training infrastructure using Python and PyTorch.
Member of Technical Staff - Post-Training
AI research lab Reflection is hiring a Member of Technical Staff (Post-Training) in London to turn pre-trained LLMs into aligned, general agents — building data generation pipelines, reward models, RL algorithms, and inference-time scaling. Requires strong ML fundamentals, large-scale LLM training experience, and solid engineering skills.
Founding Member of Technical Staff
Founding engineer at Nabi, an AI-native health system for conditions like eating disorders, building backend services, APIs, and data pipelines that connect its EHR and agentic care products, plus onboarding tools and deployment/observability infrastructure. In-person role in San Francisco; stack hints include Node.js, Elixir, and TypeScript/React.
Sr. Platform Software Engineer
Senior Platform Software Engineer at Standard Template Labs, an AI-native seed-stage startup building AI-powered IT service and configuration management. Day to day: build the internal developer platform — CI/CD with GitHub Actions, AWS/EKS/Kubernetes infrastructure, observability with Datadog, and distributed systems (PostgreSQL, Kafka, Redis, Temporal).
Sr. Software Engineer
Senior Software Engineer at an AI-native seed-stage startup building an AI-driven IT Service & Configuration Management platform. Day to day: end-to-end backend ownership (APIs, data infra, LLM integration), some full-stack UI work, and helping shape architecture and DevOps practices — on-site 5 days/week in Manhattan.
Sr. Software Engineer – Infrastructure
Senior engineer owning the graph-based, multi-tenant data tier of an AI-native SaaS platform for IT service and configuration management: designing graph schemas, sharding, indexing, and fast traversal, building backend data services, and mentoring — on-site 5 days/week in the Flatiron District, Manhattan.
Staff Software Engineer
Staff Software Engineer at a stealth AI-native startup reimagining IT service management (ITSM/CMDB). Leads hands-on design of AI-native, distributed event-driven systems embedding LLMs, embeddings and graph intelligence; owns architecture end-to-end, codes deeply, and mentors engineers, on-site five days a week in Manhattan's Flatiron District.