Senior Workforce AI Solutions Engineer

The Senior Workforce AI Solutions Engineer will design, build, and deploy enterprise AI solutions that improve employee productivity, streamline workflows, and deliver measurable business value. Working closely with business stakeholders and technical teams, this role transforms qualified requests into secure, practical, and maintainable AI-powered applications. The position combines solution architecture, hands-on engineering, workflow automation, and AI agent development using enterprise platforms such as Microsoft Copilot, Copilot Studio, Claude, and ChatGPT Enterprise. The successful candidate will manage solution requests from initial scoping through implementation, testing, documentation, and handover. They will also develop reusable agents, integrations, and engineering patterns that accelerate adoption across the organization. This is a full-time remote opportunity for a technically versatile professional who balances innovation with enterprise security, governance, and responsible AI practices.

• Relevant technical experience: Background in solution architecture, software engineering, automation, cloud engineering, application integration, or a related technology discipline.

• End-to-end solution delivery: Demonstrated experience translating business requirements into technical solutions and delivering them through implementation.

• Enterprise AI platforms: Hands-on experience with one or more enterprise AI technologies, such as Microsoft Copilot, Copilot Studio, Claude, ChatGPT Enterprise, or comparable platforms.

• Integration and development skills: Experience working with APIs, SDKs, automation technologies, integrations, and structured or unstructured enterprise data sources.

• Identity and security knowledge: Working knowledge of enterprise authentication, authorization, identity management, and secure integration patterns.

• Low-code and pro-code development: Ability to build solutions using both low-code platforms and traditional development tools, selecting the right approach for each use case.

• AI agent development: Experience building custom agents, AI assistants, agent actions, or multi-step AI workflows is preferred.

• MCP and platform extensibility: Familiarity with MCP servers, custom skills, plugins, connectors, or comparable extensibility components is preferred.

• Microsoft ecosystem expertise: Experience with Microsoft Graph, REST APIs, Azure Functions, Logic Apps, Power Automate, GitHub, Visual Studio, or Visual Studio Code is an advantage.

• Enterprise knowledge retrieval: Familiarity with retrieval-augmented generation (RAG), enterprise search, grounding, vector search, and knowledge management patterns is preferred.

• Responsible AI practices: Understanding of AI governance, data protection, security, compliance, auditability, and responsible AI implementation.

• Business value measurement: Experience identifying and measuring improvements in productivity, process efficiency, service quality, or business outcomes is beneficial.

• Analytical problem-solving: Strong troubleshooting, analytical, and solution-design skills, with the ability to evaluate trade-offs and simplify complex problems.

• Stakeholder communication: Excellent consulting, documentation, and communication skills, including the ability to explain technical concepts clearly to business and technical audiences.

• Organization and accountability: Ability to manage multiple requests, balance business urgency against technical risk, prioritize effectively, and drive work to completion with minimal supervision.

• Adaptability and curiosity: A proactive, learning-oriented mindset and enthusiasm for emerging AI capabilities, combined with disciplined engineering judgment and a strong sense of ownership.