Forward Deployed Engineer, Life Sciences

Domino Data Lab

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

Posted 11/2/2026full-timeRemote • GermanyMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Python and cloud architecture, with a strong focus on building and deploying AI solutions and machine learning workflows. Proven ability to engage with technical and business stakeholders while navigating compliance and security challenges in regulated environments.

Highest-signal resume keywords

Python ProficiencyMachine Learning WorkflowsKubernetes ExperienceCloud Architecture (AWS, Azure, GCP)Exceptional Communication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLRBashKubernetesDockerMachine LearningModel DeploymentGenerative AIStatistical Computing

Soft Skills

Exceptional CommunicationOwnership-Oriented ApproachComfortable with Ambiguity

Tools & Technologies

AWSAzureGCPEKSAKSGKE

Industry Keywords

Life SciencesRegulated EnvironmentsData SecurityCompliance

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
Take full ownership of strategic life sciences customer engagements
Execute independently against a prioritized backlog managed by the Engagement Manager
Build and deploy production-grade 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
Improve delivery speed across the Forward Deployed Engineer practice
Translate field intelligence into product feedback for SRE, Support, and Product teams
Build and deploy AI solutions including inferencing workflows, cloud and data integrations, interactive applications, Statistical Computing Environments, and clinical CRM solutions

Requirements

What you’ll need

Strong engineering roots with deep proficiency in Python
Familiarity with SQL, R, and Bash
Experience with Kubernetes and managed Kubernetes solutions such as EKS, AKS, or GKE
Experience with Docker and cloud architecture on 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
Comfortable running structured discovery conversations and leading technical solutioning sessions
Ability to translate customer requirements into buildable, tested solutions
Action-first, ownership-oriented approach; comfortable with ambiguity and unfamiliar codebases

Benefits

Comp & perks

Encouragement of diversity and inclusion across backgrounds, genders, ethnicities, abilities, and sexual orientations
Growth mindset and opportunities for teaching and learning
Environment emphasizing employee development and equipping employees with tools for success