Forward Deployed Engineer

About

About Dynamo AI

Security, hallucination, and compliance gaps are stifling your AI production goals. Dynamo delivers auditable AI guardrails, hallucination checks, red-teaming, and observability so you can productionize AI with confidence.

About the role

Dynamo AI is hiring a Forward Deployed Engineer to work directly with enterprise customers to deploy, integrate, and operationalize AI systems in real-world production environments. This role sits at the intersection of engineering, customer deployment, and AI reliability. You'd be the 3rd FDE globally, joining colleagues in Japan and on the West Coast US. This hire covers East Coast US or Europe and works with 3-4 customers concurrently. You'd act as the technical bridge between customers and Dynamo AI's product and engineering teams, helping customers implement AI guardrails, evaluation systems, observability workflows, and deployment architectures that meet enterprise requirements around reliability, security, compliance, and performance. Many customers operate highly regulated systems with deeply embedded existing infrastructure, approval workflows, and operational constraints. Success requires understanding these environments deeply, collaborating through ambiguity, and helping customers incrementally operationalize AI safely and effectively.

What you'll own

• Lead deployments of Dynamo AI products into customer environments: EKS, AKS, GKE, OpenShift, and on-prem Kubernetes clusters
• Work directly with customer engineering, security, infrastructure, and operations teams across networking, identity, storage, observability, scaling, security, and reliability
• Troubleshoot production and pre-production issues across Kubernetes, application services, databases, ingress, authentication, networking, and cloud infrastructure
• Build deployment automation, Helm configurations, scripts, runbooks, and validation workflows
• Drive technical scoping, effort estimation, risk assessment, rollout planning, and production readiness reviews
• Partner with product and engineering teams to surface deployment patterns, integration gaps, and customer-driven improvements

Requirements

Must-have

• 3-8 years post-undergrad in software engineering, infrastructure engineering, platform engineering, solutions engineering, or customer-facing engineering (1+ year post-grad with master's also acceptable)
• Strong hands-on Kubernetes production experience plus at least one major cloud (AWS, Azure, or GCP)
• Infra engineer or DevOps background at a startup, solutions company, or consulting firm. Traditional DevOps from banks or other "traditional sector" companies is a hard exclusion per the hiring manager.
• Customer-facing deployment experience: comfortable interfacing with customer engineering, security, and compliance teams
• Comfortable with East Coast US or UK time zones, with availability for twice-weekly evening calls to collaborate with the India team

Nice-to-have

• Master's or beyond in Computer Science, Engineering, or related field
• Familiarity with Generative AI systems, LLM applications, AI infrastructure, or model deployment workflows
• Experience working in financial services, healthcare, government, or other regulated industries
• Identity and access systems experience (OIDC, SAML, Keycloak, Entra ID, Okta)
• AI evaluation, guardrails, observability, or monitoring systems background
• Prior FDE, Solutions Engineering, or Implementation Engineering at a high-growth AI infrastructure or AI tooling startup

Benefits & perks

• Fully Remote

Interview process

1. 1Application review
2. 2Initial Screen
3. 3Round 1 Technical
4. 4Round 2 Mock Customer Deployment
5. 5Round 3 Domain Expertise + Behavioral
6. 6Founder Round
7. 7Offer Extended
8. 8Hired