Senior Software Engineer - AI Platforms (MN)

Our firm is partnering with a global leader in the manufacturing and equipment industry to hire a Senior Software Engineer, AI Platforms. This organization develops products, technologies, and services used across construction, agriculture, landscaping, and related industries worldwide. This is a senior-level role focused on building, scaling, and operating enterprise AI platforms across a global organization. The position combines hands-on software engineering with AI platform ownership, DevSecOps, enterprise integrations, governance, and technical enablement. Approximately 50% of the role will focus on hands-on engineering and 50% on platform ownership and operations. The ideal candidate is a strong problem solver who is comfortable working through ambiguity, translating loosely defined business requests into practical technical solutions, and guiding stakeholders toward secure and scalable approaches. This person should be comfortable challenging requests that do not align with technical standards, security requirements, or organizational policies while offering viable alternatives. This is an AI platform engineering role and does not require a data science background., * Serve as the technical owner and lead administrator for enterprise AI platforms, including configuration, identity and access integration, onboarding, lifecycle management, monitoring, operational support, and continuous improvement.

• Lead the global rollout and ongoing operation of AI platforms, establishing scalable processes for provisioning, access management, adoption, support, and governance.
• Design and develop integrations between AI platforms and existing enterprise systems using APIs, connectors, MCP servers, automation, and related integration technologies.
• Implement DevSecOps practices across AI platform environments, including secure coding, CI/CD, secrets management, dependency management, vulnerability management, software supply chain controls, logging, and security validation.
• Partner with security and AI transformation teams to implement AI governance practices related to identity, access, data protection, auditability, guardrails, risk controls, and responsible AI.
• Build the technical ecosystem needed to support enterprise AI builders and agentic software engineering, including reusable components, reference implementations, development standards, documentation, self-service capabilities, and troubleshooting resources.
• Define and monitor platform health, reliability, performance, security, usage, and adoption metrics and proactively identify opportunities for improvement.
• Troubleshoot complex platform, integration, deployment, performance, infrastructure, and security issues across cloud and enterprise environments.
• Develop technical designs, architecture documentation, operating procedures, support models, engineering standards, and platform roadmaps.
• Lead technical initiatives, contribute to architecture decisions, mentor engineers, and help establish platform engineering standards and best practices.
• Partner across engineering, infrastructure, security, enterprise architecture, legal, privacy, procurement, and business teams to support responsible AI adoption.
• Evaluate ambiguous or incomplete requests, identify the underlying business or technical need, and recommend secure and supportable solutions.
• Provide technical guidance and coaching to stakeholders, including communicating when proposed solutions are not technically feasible or do not align with established security or governance requirements.

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical field, or equivalent practical experience.
• 7+ years of professional experience in software engineering, platform engineering, DevOps, DevSecOps, cloud engineering, or a closely related discipline.
• Hands-on software development experience with Python or a comparable programming language, including experience building APIs, automation, and system integrations.
• Hands-on experience applying generative AI technologies in production or working solutions, which may include large language models (LLMs), AI assistants, prompt engineering, retrieval-augmented generation (RAG), AI agents, model APIs, or AI-enabled applications.
• Experience building, scaling, and operating enterprise software platforms or shared services in cloud or hybrid environments.
• Demonstrated DevSecOps experience with source control, CI/CD, Infrastructure as Code (IaC), automated testing, release management, observability, and operational automation.
• Experience implementing secure software delivery practices, including identity and access management (IAM), secrets management, vulnerability management, dependency management, security testing, audit logging, and software supply chain controls.
• Working knowledge of at least one major cloud platform, such as Microsoft Azure, AWS, or Google Cloud Platform (GCP), including cloud-native architecture and operations.
• Ability to independently diagnose complex issues across application, platform, integration, cloud, infrastructure, and security layers.
• Ability to take ambiguous or loosely defined requests, determine the underlying need, and translate requirements into secure, scalable, and supportable technical solutions.
• Strong judgment and communication skills, including the ability to professionally challenge requests that do not align with security, governance, technical, or organizational requirements and recommend appropriate alternatives.
• Strong written and verbal communication skills with the ability to communicate technical decisions, risks, and trade-offs to technical and nontechnical stakeholders.
• Demonstrated technical leadership through initiative ownership, mentoring, coaching, architectural input, and influence across engineering teams.
• Strong cross-functional collaboration skills with experience working across engineering, infrastructure, security, architecture, and business teams in Agile environments.
• Ability to travel less than 10%.

Preferred

• Experience owning or administering an enterprise AI or generative AI platform at scale.
• Experience supporting the enterprise-wide or global rollout of shared technology platforms.
• Experience with AI agents, agentic software engineering, retrieval-augmented generation (RAG), LLM integrations, and model APIs.
• Experience developing enterprise integrations using MCP servers, APIs, connectors, or similar integration technologies.
• Experience establishing reusable components, reference architectures, development standards, or self-service tooling for internal engineering teams.
• Familiarity with responsible AI, AI governance, data protection, security guardrails, and auditability in enterprise environments.
• Experience monitoring and improving platform reliability, performance, security, adoption, and operational health.
• Experience influencing architecture and platform standards across multiple engineering or business teams without direct people-management responsibility.

Dahl Consulting is proud to offer a comprehensive benefits package to eligible employees that will allow you to choose the best coverage to meet your family’s needs. For details, please review the DAHL Benefits Summary: https://www.dahlconsulting.com/benefits-w2fta/.