Senior Forward Deployed Engineer- Intelligent Engineering

Gradera•Des Moines, IA

6d•Onsite

About The Position

Gradera is an AI-native transformation services company helping enterprises accelerate AI adoption in a governed, reliable, and scalable way. We combine enterprise transformation experience, deep domain knowledge, product engineering expertise, AI-native methods, and a global delivery model to create measurable business outcomes. Gradera’s Intelligent Engineering capabilities help enterprises create, modernize, and operate software using AI-first engineering methods. Rather than simply adding AI tools to existing development practices, we help clients redesign engineering workflows, teams, environments, and delivery practices for AI-enabled and agentic software engineering. The Senior Forward Deployed Engineer – Intelligent Engineering is a senior client-facing technologist who operates at the intersection of business process, solution architecture, AI-native engineering, and hands-on implementation. The role is designed for someone who can enter a complex enterprise environment, quickly understand how software is planned, built, tested, integrated, deployed, and operated, identify gaps and opportunities, and translate those findings into working solutions using Gradera’s Intelligent Engineering capabilities and the client’s existing technology ecosystem. This is not a traditional advisory or architecture-only role. The Senior FDE must be equally comfortable assessing an enterprise engineering environment, defining the target solution, and personally moving into implementation. The individual should be able to operate independently with client technology and business stakeholders while connecting field learning back into Gradera’s Intelligent Engineering Studio. Successful Senior FDEs help clients solve the immediate problem while identifying reusable patterns, capability gaps, and expansion opportunities that strengthen both the client relationship and Gradera’s Intelligent Engineering portfolio.

Requirements

Demonstrated experience entering an unfamiliar enterprise environment, rapidly understanding the architecture and engineering landscape, and independently identifying a path forward.
Solution architecture skills combined with current hands-on software engineering capability; this role requires someone who can personally move from architecture and design into implementation.
Ability to move fluidly between executive/architectural discussions and detailed technical implementation.
Experience assessing and improving SDLC, DevEx, testing, integration and deployment practices—not simply building an application within an already-defined architecture.
Experience working directly with enterprise clients in a consulting, field engineering, solution architecture, professional services or similar role.
Ability to identify reusable patterns from client implementations and translate field experience into repeatable engineering capabilities.
Technical judgment; comfortable determining what can be solved with an existing capability versus where a new solution or pattern must be created.
Ability to operate with ambiguity and limited supervision in complex client environments.
Experience designing and delivering solutions using the Microsoft technology ecosystem, including Power Platform, Copilot Studio, Visual Studio Code, and GitHub Copilot.
Experience with AI-native and agentic software engineering methods, AI-DLC or equivalent.
Proven understanding of APIs, application integrations, data flows, and enterprise system connectivity.
Experience implementing automated testing frameworks, including Playwright, and utilizing CI/CD pipelines and deployment automation.
Familiarity with Azure DevOps and modern software delivery practices from requirements management through deployment.
Demonstrated ability related to problem-solving, communication, and stakeholder engagement skills.

Responsibilities

Assess client engineering environments across architecture, applications, developer tooling, requirements, testing, integrations, CI/CD, deployment, data flows, AI-enabled engineering practices, and operational controls.
Develop a practical understanding of the client’s business processes and operating context so engineering recommendations address business outcomes rather than technology in isolation.
Identify gaps, constraints, and engineering opportunities across Create, Modernize, and Operate scenarios and map them to Gradera Intelligent Engineering Service Products, reusable Studio components, and delivery patterns.
Translate findings into solution architectures, technical backlogs, implementation plans, and production-ready software.
Operate as both architect and hands-on engineer, moving from high-level solution design into configuration, coding, integration, testing, deployment, troubleshooting, and optimization.
Implement AI-native engineering solutions using Gradera methods and capabilities together with client platforms, development environments, AI tooling, automation, and agentic engineering frameworks.
Evaluate architecture and engineering practices, identify risks and missing capabilities, recommend improvements, and take those recommendations through implementation.
Serve as a field-to-Studio feedback loop by identifying reusable implementation patterns, emerging client needs, capability gaps, and opportunities that should inform the continued evolution of Gradera’s Intelligent Engineering Studio and Service Products.
Recognize opportunities where additional Intelligent Engineering capabilities or delivery squads can accelerate client outcomes and partner with Gradera Client Solutions and Delivery teams to shape expansion.
Build trusted relationships across business, architecture, engineering, product, and delivery stakeholders and act as the bridge between business need and executable technical solution.