Forward Deployed Engineer

Nexus Cognitive

. Embed with strategic customers from post-sale discovery through production rollout, stabilization, and knowledge transfer .

Posted 9/23/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing, building, and deploying customer-specific integrations and data pipelines while ensuring production readiness across various environments. Proficient in troubleshooting distributed systems and leading technical workstreams to resolve high-severity issues.

Highest-signal resume keywords

Production Proficiency In Python, Java, Scala, Or GoStrong Kubernetes And Container ExperienceExperience With Modern Data Infrastructure And Distributed SystemsWorking Knowledge Of AWS, Azure, Or GCPExperience Deploying Data Platforms In Regulated Industries

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringData EngineeringInfrastructure EngineeringProduction Systems OwnershipIntegration DesignData Pipeline DevelopmentAI-Enabled WorkflowsInfrastructure-As-CodeTroubleshooting Distributed SystemsPerformance Engineering

Soft Skills

Excellent Written And Verbal CommunicationHigh AgencySound JudgmentLow EgoComfort Operating In Ambiguous Environments

Tools & Technologies

KubernetesTerraformSparkKafkaAirflowTrino/PrestoIcebergCloud Data PlatformsIAM/RBACData Lakes

Industry Keywords

Post-Sales EngineeringProfessional ServicesSolutions DeliveryCompliance ControlsChange ManagementDisaster RecoverySecurity HardeningIncident ResponseHybrid-Cloud EnvironmentsEnterprise Identity

Tech Stack

Tools & technologies

AirflowAWSAzureCloudDistributed SystemsGoogle Cloud PlatformJavaKafkaKubernetesPythonScalaSparkTerraformGo

About the role

Key responsibilities & impact

Embed with strategic customers from post-sale discovery through production rollout, stabilization, and knowledge transfer
Translate business outcomes and ambiguous customer requirements into technical designs, milestones, and working software
Design, build, test, and deploy customer-specific integrations, data pipelines, platform extensions, migration utilities, and AI-enabled workflows
Integrate NexusOne with enterprise identity, security, governance, data catalog, storage, compute, orchestration, observability, and CI/CD systems
Support migrations and modernization across on-premises, private-cloud, public-cloud, and hybrid environments
Establish production-readiness criteria for performance, reliability, security, disaster recovery, monitoring, and operational ownership
Write production-quality code and deploy and troubleshoot distributed systems on Kubernetes using infrastructure-as-code
Diagnose issues across application code, data pipelines, networking, IAM/RBAC, certificates, storage, compute, and customer infrastructure
Lead technical workstreams during high-severity deployment issues and drive root-cause resolution
Produce architecture diagrams, design documents, implementation plans, runbooks, test plans, decision logs, and post-incident reviews
Lead technical workshops, design reviews, whiteboarding sessions, and hands-on enablement
Pair with customer engineers and architects to enable independent operation of solutions
Provide structured field feedback to Product and Engineering
Convert repeated work into reusable connectors, reference architectures, deployment automation, tests, templates, and playbooks
Contribute product-level improvements to the core platform
Create clean handoffs to Customer Reliability Engineering and Support

Requirements

What you’ll need

6+ years of professional software, platform, data, or infrastructure engineering experience, including substantial hands-on ownership of production systems
Experience in a customer-facing post-sales, professional services, solutions delivery, consulting engineering, resident engineering, or forward-deployed role—or equivalent experience working directly with enterprise users
Production proficiency in at least one backend language such as Python, Java, Scala, or Go
Experience with modern data infrastructure and distributed systems, such as Spark, Trino/Presto, Iceberg, Kafka, Airflow, dbt, data lakes, or cloud data platforms
Strong Kubernetes and container experience, including deployment, troubleshooting, configuration, networking, observability, and operational readiness
Working knowledge of at least one major cloud platform (AWS, Azure, or GCP) and infrastructure-as-code practices such as Terraform
Ability to troubleshoot across system boundaries and resolve underlying problems
Experience with enterprise constraints including security reviews, IAM/RBAC, private networking, compliance controls, change management, and multiple stakeholder groups
Excellent written and verbal communication
High agency, sound judgment, low ego, and comfort operating in ambiguous environments
Willingness to travel to customer sites as engagements require
Experience deploying data platforms in regulated industries, on-premises or hybrid-cloud environments, legacy data estates, production AI applications, performance engineering, high availability, disaster recovery, security hardening, or incident response are strong differentiators

Benefits

Comp & perks

Collaborative team culture built on curiosity and respect
Challenging work where contributions clearly matter
Leadership team that invests in learning and development
Opportunity to work at the intersection of cloud, data, and AI innovation