Forward Deployed Engineer

Domino Data Lab

. Master Domino platform mechanics and core user/admin functionalities during onboarding .

Posted 11/2/2026full-timeRemote • New York • United StatesJunior💰 $165,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying AI solutions across the MLOps lifecycle, with strong proficiency in Python and familiarity with SQL, R, and Bash. Capable of navigating compliance requirements and delivering machine learning workflows while effectively communicating with both technical and business stakeholders.

Highest-signal resume keywords

Python ProficiencyMLOps Lifecycle ManagementKubernetes ExperienceCloud Architecture (AWS, Azure, GCP)Customer-Facing Technical Role

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLRBashKubernetesDockerAWSAzureGCPMachine Learning Workflows

Soft Skills

Exceptional Communication SkillsStructured Discovery ConversationsTechnical Solutioning LeadershipAbility to Thrive in Ambiguity

Tools & Technologies

Domino PlatformCI/CDCloud IntegrationsInteractive ApplicationsDeployment Guides

Industry Keywords

ComplianceData SecurityGovernanceRegulated EnvironmentsTechnical Stakeholders

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonSQL

About the role

Key responsibilities & impact

Master Domino platform mechanics and core user/admin functionalities during onboarding
Shadow customer environments and pair with a senior Forward Deployed Engineer
Learn customers’ data, tooling stacks, and commercial objectives
Take full ownership of customer engagements and execute against prioritized backlogs managed by an Engagement Manager
Build and deploy production-grade AI solutions across the MLOps lifecycle, including development, deployment, and monitoring
Advise data science teams on Domino best practices
Lead and advise key accounts as a trusted advisor to technical and business stakeholders
Author reusable playbooks, integration templates, and deployment guides
Translate field intelligence into product feedback for SRE, Support, and Product teams
Build and deploy specialized AI and inference workflows, custom cloud and data integrations, interactive applications, CI/CD and platform extensions, and solutions meeting strict security, compliance, and governance requirements

Requirements

What you’ll need

1-3 years of experience working in a customer-facing technical role
Strong engineering roots with deep proficiency in Python
Familiarity with SQL, R, and Bash
Experience with Kubernetes and managed K8s solutions such as EKS, AKS, or GKE
Experience with Docker and cloud architecture using AWS, Azure, or GCP
Ability to troubleshoot networking, compute, and platform issues
Proven track record delivering machine learning workflows, model deployment and monitoring, GPU workloads, and generative AI or agent frameworks
Experience operating within or consulting for highly regulated or constrained environments
Ability to navigate strict compliance rules, data security hurdles, and infrastructure limits
Exceptional communication skills across technical and business audiences
Ability to run structured discovery conversations and lead technical solutioning sessions
Ability to translate customer requirements into buildable, tested solutions
Ability to thrive in ambiguity and become productive quickly inside an unfamiliar codebase

Benefits

Comp & perks

Equity
Company bonus or sales commissions/bonuses
401(k) plan
Medical, dental, and vision benefits
Wellness stipends
Visa sponsorship may be available depending on business considerations and role requirements