Forward Deployed AI Engineer

A large enterprise organization is seeking a hands-on Forward Deployed AI Engineer to join its growing Enterprise AI team. This role will work directly with employees across departments to uncover operational challenges and rapidly transform them into practical AI-powered applications, automations, and internal tools.

Unlike a traditional development role centered around a predefined backlog, this position requires embedding with business teams, observing how work is performed, identifying inefficiencies, and proactively developing solutions.

The ideal candidate combines software engineering fundamentals with curiosity, strong business instincts, and a user-focused mindset. You should be comfortable developing in Python and/or C#/.NET, using AI-assisted coding tools to accelerate delivery, and working through loosely defined requirements.

Success will be measured by your ability to understand users, build practical solutions quickly, iterate based on feedback, and deliver measurable business value., * Embed with business teams to understand workflows, identify pain points, and uncover opportunities for AI, automation, or application development.

• Lead discovery conversations with users who may not know how to translate their challenges into technical requirements.
• Turn ambiguous business problems into functional prototypes and production-ready solutions.
• Rapidly build and iterate using Python, C#/.NET, AI-assisted development tools, or a combination of traditional and AI-generated code.
• Develop AI-enabled applications, copilots, agents, search tools, workflow automations, and full-stack business solutions.
• Demonstrate early versions to users, gather feedback, and continuously improve the product.
• Determine when AI is appropriate and when a traditional application, integration, or automation would provide a better solution.
• Integrate applications with enterprise data sources, APIs, databases, documents, and existing business systems.
• Communicate technical concepts, limitations, risks, and tradeoffs in language business users can understand.
• Evaluate AI outputs for accuracy, reliability, security, and alignment with business requirements.
• Own solutions throughout the full lifecycle, including discovery, development, testing, deployment, adoption, and ongoing enhancement.
• Adapt quickly as business needs and executive priorities evolve.

• Strong software engineering foundation using Python and/or C#/.NET.
• Experience developing applications, internal tools, workflow automations, or AI-powered solutions.
• Experience using modern AI development and coding tools to accelerate prototyping and delivery.
• Ability to work across the technology stack, including backend services, APIs, databases, integrations, and user-facing applications.
• Practical understanding of LLMs and AI application patterns, including:
• Retrieval-augmented generation (RAG)
• AI agents and tool calling
• Semantic or vector search
• Prompt engineering
• Chatbots and copilots
• AI output evaluation and validation
• Cloud development experience in Azure, AWS, or GCP; Azure is preferred.
• Ability to work directly with nontechnical users and translate loosely defined needs into functional solutions.
• Strong communication, listening, presentation, and relationship-building skills.
• Demonstrated ownership, curiosity, adaptability, and comfort operating without perfectly defined requirements.
• Ability to work onsite five days per week and spend time embedded with different business teams., * Experience in a forward deployed engineering, solutions engineering, field engineering, technical consulting, innovation, or rapid-prototyping role.
• Experience within oil and gas, energy, industrial, manufacturing, or another asset-intensive environment.
• Familiarity with workflows across Operations, Engineering, Commercial, Finance, HR, Compliance, or Field Services.
• Experience deploying AI applications within secure enterprise environments.
• Experience with Azure technologies such as:
• Azure OpenAI
• Azure AI Foundry
• Azure Functions
• Azure Service Bus
• Azure API Management
• Azure AI Search
• Microsoft Entra ID
• Experience with technologies such as SQL Server, SharePoint, Databricks, Blazor, ASP.NET Core, Semantic Kernel, Copilot Studio, or other agent frameworks.
• Experience connecting AI applications to enterprise documents and structured or unstructured data.
• AI certifications, personal projects, hackathon experience, or other evidence of continued experimentation with emerging technology.

The strongest candidate will be:

• Business-minded: Focused on solving the user’s problem rather than applying technology for its own sake.
• Technically resourceful: Able to build independently and use AI tools to increase speed and productivity.
• User-facing: Comfortable sitting alongside employees, asking thoughtful questions, observing their work, and earning their trust.
• Consultative: Able to uncover the real business need, even when the initial request is vague or points toward the wrong solution.
• Action-oriented: Moves quickly from discovery to prototype without waiting for perfectly documented requirements.
• Adaptable: Comfortable shifting between technologies, business functions, and evolving priorities.
• Pragmatic: Understands when to use an LLM, automate a workflow, integrate an existing system, or build a traditional application.
• Outcome-focused: Can explain what was built, who used it, what problem it solved, and the business impact it delivered.
• End-to-end: Takes ownership beyond development, including testing, deployment, adoption, iteration, and production reliability.