Forward Deployed Engineer – Data and AI Platform Integrations

Forward Deployed Engineer – Data and AI Platform Integrations

This role is with a DeWinter AI Platform Partner

100% remote

12 Month+ contract (or contract to hire, if desired)

Position Overview

We are seeking a customer-facing Forward Deployed Engineer to help enterprise customers implement and operationalize a sophisticated data, AI and governance platform.

This position sits at the intersection of engineering, technical consulting and post-sales delivery. You will work directly with customer engineering, infrastructure, data and security teams to understand their environments, develop deployment strategies, integrate the platform with their existing technology and guide them through production adoption.

This is not a traditional account management or project coordination position. You must be a hands-on engineer who is comfortable working directly with customers and solving complex technical integration and deployment challenges.

Responsibilities

• Lead technical onboarding and implementation for enterprise customers.
• Work directly with customer data, infrastructure, security and engineering teams.
• Understand each customer’s architecture, operational requirements, security constraints and data-sovereignty needs.
• Design deployment strategies across cloud, on-premises and hybrid environments.
• Help customers prepare, aggregate and integrate trusted data layers for AI and analytics use cases.
• Configure and integrate data-processing, orchestration, security, identity and governance technologies.
• Support Kubernetes-based deployments and troubleshoot infrastructure or configuration issues.
• Advise customers on AI-agent configuration, security policies, governance and production best practices.
• Diagnose complex issues across the customer’s data, application, infrastructure and security ecosystem.
• Coordinate with internal product and engineering teams while independently resolving implementation challenges.
• Document deployment patterns, technical decisions and reusable implementation practices.
• Help move customers from proof of value through production deployment and long-term adoption.

Required Experience

• Strong hands-on background in data engineering, platform engineering, systems integration or distributed systems.
• Experience implementing complex software platforms in customer environments.
• Proficiency with technologies such as Apache Spark, Trino and Airflow.
• Strong understanding of Kubernetes and containerized application deployments.
• Experience working with cloud, on-premises and hybrid infrastructure.
• Knowledge of modern data architectures, including data lake, lakehouse and curated or gold-layer concepts.
• Experience integrating APIs, databases, data pipelines and enterprise systems.
• Strong troubleshooting skills across applications, infrastructure, data and security.
• Ability to communicate effectively with technical and nontechnical customer stakeholders.
• Experience translating customer requirements into practical technical solutions.
• Ability to work independently in a fast-moving, high-growth environment.

Preferred Experience

• Apache Ranger, Keycloak or similar security, governance and identity technologies.
• dbt, Fivetran, Airbyte or comparable data-transformation and integration tools.
• Open-source AI or data infrastructure.
• AI governance, policy management or enterprise agent deployment.
• Data-sovereignty, privacy and regulatory requirements.
• Experience supporting banks, insurance providers or other regulated enterprises.
• Background in professional services, technical consulting, solutions architecture, technical account management or forward deployed engineering.
• Experience supporting customers across the United Kingdom and European Union.

Ideal Candidate

The ideal candidate is an engineer who enjoys working at the front of the house. You can sit with a customer, understand a complex technical environment, design an implementation approach and remain hands-on through deployment and troubleshooting.

You are equally comfortable discussing architecture with senior technical leaders, working through configuration issues with engineers and explaining risks or tradeoffs to business stakeholders.