Forward Deployed Engineer (FDE)

Seaboard Corporation•Merriam, KS

6d•Onsite

About The Position

Seaboard Energy is hiring a build-first Forward Deployed Engineer to support its Energy business, based out of the Merriam, Kansas office. The position combines hands-on data and software development with delivery coordination and the establishment of technical patterns and standards. Approximately 70–80% of the role is hands-on building with a data platform and AI-Assisted Development, 10% is orchestrating delivery, and 10–20% is setting and operationalizing technical standards. The engineer leads through the work, delivering complex, high-impact parts of initiatives and turning solutions into reusable patterns for the team. The role owns delivery of complex data and AI initiatives from scoping and design through implementation, testing, and rollout. Work includes gathering, ingesting, transforming, and serving data; developing pipelines, lakehouses, semantic models, and OneLake medallion structures; building and consuming APIs; extending a business ontology in Foundry and AIP; and creating applications, agents, and tools. The engineer embeds with Energy teams to develop domain knowledge, gather feedback, and deliver software that supports measurable business outcomes. Releases and data assets must be operationally ready, with monitoring, runbooks, deployment approaches, and escalation paths in place. The engineer also coordinates initiative cadence and dependencies across Energy, IT, and external vendors; clarifies priorities and confirms direction with sponsoring leaders; and establishes reusable patterns for AI-Assisted Development, data pipeline and semantic-model design, API integration, and ontology modeling. The role includes design and implementation reviews, mentoring, and documenting or retiring technical patterns as appropriate.

Requirements

At least 4 years of technical delivery experience.
A track record of hands-on production software and data-pipeline delivery, including within the past 12 months.
Hands-on experience building data solutions on Microsoft Fabric or an equivalent modern cloud data platform.
Experience consuming APIs, including debugging integration failures.
Experience with data warehouse or lakehouse design patterns, including medallion architecture, data modeling, and incremental load strategies.
Hands-on proficiency with AI-Assisted Development.
Familiarity with cloud platforms such as Azure or AWS and modern DevOps and CI/CD practices.
Ability to establish technical patterns and standards that other engineers adopt.
Ability to lead cross-team initiatives, manage stakeholders, and operate in ambiguous situations to drive outcomes.
Ability to break large problems into small deliverable increments and maintain momentum and transparency through frequent releases.
Understanding of business operations and ability to connect data and architecture decisions to business outcomes.

Nice To Haves

Knowledge of Foundry and AIP, including ontology, AIP Logic, Workshop, and Pipeline Builder, or equivalent enterprise data and ontology platform experience with ability to ramp quickly.
Background in the liquid fuels or oil and gas industry.
Background in manufacturing, logistics, or commodities.
Experience with Microsoft Fabric workloads, including Lakehouse, Data Warehouse, Dataflows Gen2, Notebooks, Pipelines, and/or Real-time Intelligence.
Experience with PySpark, SQL, and Python for production-scale data engineering.
Experience building and maintaining semantic models.
Experience with Azure API Management, Azure Functions, or other Azure integration services.
Degree in Computer Science, Information Systems, Data Engineering, or a related field.

Responsibilities

Own end-to-end delivery of complex Energy data and AI initiatives, from scoping and design through build, test, and rollout.
Gather, ingest, transform, and serve business data by building data pipelines, lakehouses, semantic models, and OneLake medallion structures.
Build, consume, and maintain APIs, including designing contracts, implementing endpoints, and integrating internal systems and external vendors.
Model and extend the business ontology in Foundry and AIP, including objects, links, actions, and write-back paths.
Build applications, agents, and tools on the ontology and data platform to improve Energy business operations.
Embed with Energy teams, build domain knowledge, iterate with stakeholders, and deliver software tied to measurable business outcomes.
Ensure releases and data assets are operationally ready with monitoring, runbooks, deployment approaches, and escalation paths.
Stay current on data platforms, AI tools, agent and ontology platforms, and modern delivery practices, applying proven patterns to the work.
Run or participate in standups, working sessions, and lightweight planning for milestones, dependencies, and cutovers.
Coordinate across Energy, IT teams, and external vendors to identify and resolve blockers.
Clarify priorities by bringing stakeholders together, facilitating trade-off discussions, and confirming direction with sponsoring leaders.
Set reusable standards for AI-Assisted Development, data pipelines, semantic models, API integration, and ontology modeling.
Conduct design and implementation reviews to improve quality and reduce long-term support burden.
Mentor colleagues through pairing, code reviews, and coaching.
Document the rationale for technical choices and retire patterns that are no longer effective.