Forward Deployed Engineer, Life Sciences

Domino Data Lab

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

Posted 11/3/2026full-timeRemote • SpainMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Python programming and MLOps lifecycle management, with a strong ability to build and deploy production-grade solutions. Proven experience in navigating compliance and security in regulated environments while effectively communicating with both technical and business stakeholders.

Highest-signal resume keywords

Python ProficiencyMLOps Lifecycle ManagementKubernetes ExperienceCloud Architecture (AWS, Azure, GCP)Machine Learning Workflow Delivery

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLRBashKubernetesDockerMachine LearningModel DeploymentGenerative AIAI Workflows

Soft Skills

Exceptional CommunicationStructured Discovery ConversationsTechnical Solutioning LeadershipAction-First MentalityAbility to Thrive in Ambiguity

Tools & Technologies

Domino PlatformEKSAKSGKECloud IntegrationsClinical CRM

Industry Keywords

Life SciencesRegulated EnvironmentsData SecurityComplianceInfrastructure Limits

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonSQL

About the role

Key responsibilities & impact

Master Domino platform mechanics and core user/admin functionalities
Shadow customer environments and pair with a senior Forward Deployed Engineer
Take ownership of strategic life sciences customer accounts
Execute independently against prioritized backlogs managed by an 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
Translate field intelligence into product feedback for SRE, Support, and Product teams
Build AI workflows, specialized AI inferencing workflows, custom cloud and data integrations, interactive applications, and solutions involving SCE and clinical CRM

Requirements

What you’ll need

Strong engineering roots with deep proficiency in Python (primary), alongside 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 (AWS, Azure, or GCP)
Ability to troubleshoot networking, compute, and platform issues
Proven track record of delivering machine learning workflows, model deployment/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 mentality; ability to thrive in ambiguity and become productive quickly in unfamiliar codebases

Benefits

Comp & perks

Diverse and inclusive workplace
Teaching and learning environment to equip employees with tools for success
Growth mindset and opportunities for improvement