David Joseph & Company
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Type: Full-time | Remote | UK / New York City, NY / Massachusetts, US / Florida, US Compensation: $150,000–$200,000 + Competitive Equity Hiring count: 1 Visa sponsorship: None available Reports to: Not specified on role page (Oliver runs the initial screen and the domain/behavioral round)
Dynamo AI helps enterprises deploy AI systems that are reliable, secure, observable, scalable, and production-ready — providing the infrastructure, evaluation frameworks, and real-time guardrails that let enterprises operationalize Generative AI at scale. It works with regulated industries — banks, government agencies, insurance companies, and other regulated enterprises, from Fortune 500 companies to top global banks. Flagship products are DynamoEval (evaluation frameworks), DynamoGuard (real-time guardrails), and AgentWarden (agentic observability).
Founded: 2021 | Team size: 11–50 (Series A) | Industry: AI Tools Website: https://www.dynamo.ai/
A Forward Deployed Engineer working directly with enterprise customers to deploy, integrate, and operationalize AI systems in real-world production environments — sitting at the intersection of engineering, customer deployment, and AI reliability. Covers 3–4 concurrent customers, many running highly regulated systems with deeply embedded infrastructure and approval workflows.
Tech stack: Kubernetes (EKS, AKS, GKE, OpenShift, on-prem); Helm, Terraform, ArgoCD; AWS/Azure/GCP; identity systems (OIDC, SAML, Keycloak, Entra ID, Okta); Dynamo products (DynamoEval, DynamoGuard, AgentWarden)
Salary $150,000–$200,000 Equity Competitive On-site policy Fully remote (UK / NYC / MA / FL); East Coast US or UK hours; twice-weekly evening calls with India team Visa sponsorship None available Employment type Full-time Location Remote — UK / New York City, NY / Massachusetts / Florida
Stage 1 — Pending Approval — Candidates awaiting initial approval. Stage 2 — Initial Screen with Oliver (30 min) — Non-technical introduction. Stage 3 — Round 1 Technical with Yash — Basic knowledge questions on Kubernetes, networking, and DevOps. Stage 4 — Round 2 Mock Customer Deployment with Edwin — Hands-on access to a Kubernetes cluster; complete a deployment task with the interviewer. Given access to a new service and asked to extend, debug, or adapt to it quickly. Candidates may search or use AI tools during the interview. Stage 5 — Round 3 Domain Expertise + Behavioral with Oliver — Walkthrough of previous projects with technical detail questions, plus non-technical questions on collaboration and leadership. Stage 6 — Founder Round Stage 7 — Offer Extended Stage 8 — Candidate Hired — Candidate accepts and starts.
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