Job SummaryThe Sr. AI Engineer (Forward Deployed) is a software engineer and technical consultant who works directly with business teams to solve high-value problems in their real-world operating environments. Embedded with functional stakeholders, this role translates ambiguous needs into working AI and automation solutions, guides opportunities from discovery and business-case development through prototyping, integration, governed production deployment, adoption, and value realization, and ensures that technology capabilities produce measurable business outcomes.
The initial focus will be activating and extending capabilities already available within Microsoft's enterprise AI and automation ecosystem, including Microsoft 365 Copilot, Microsoft 365 Copilot Chat, Copilot agents, Copilot Studio, Power Automate, and related capabilities. The role will then help deliver purpose-built solutions integrated with enterprise applications and, as the organization's AI maturity grows, support more advanced use cases requiring deeper AI engineering, systems integration, data, application development, and agentic solution skills. Success requires curiosity, strong consulting and facilitation skills, technical credibility, a bias for action, and a commitment to responsible AI.
Essential Duties and ResponsibilitiesThe incumbent may be asked to perform other function-related activities in addition to the below-mentioned responsibilities as reasonably required by business needs.
- Partner with leaders, functional teams, and end users to understand business goals, map current workflows, identify pain points, and define opportunities for AI and automation.
- Facilitate discovery workshops and translate business needs into clear use cases, requirements, solution options, expected benefits, risks, and success measures.
- Assess and prioritize opportunities using a standardized business case that evaluates business value, cost, feasibility, data readiness, security, compliance, user impact, risk, time-to-value, scalability, and total cost of ownership.
- Design, prototype, code, configure, test, integrate, deploy, and support AI and automation solutions using Microsoft 365 Copilot, Microsoft 365 Copilot Chat, Copilot agents, Copilot Studio, Power Platform, Azure AI services, APIs, and appropriate software-development frameworks.
- Partner with the VP, AI Transformation, Information Systems (IS), business sponsors, and applicable governance stakeholders to provide technical feasibility, architecture, effort, dependency, and delivery-risk inputs while maintaining primary accountability for solution design and implementation. Support coordinated intake, prioritization, benefits tracking, and executive reporting as the organization's AI operating model matures.
- Lead assigned solutions with a high degree of autonomy, balancing rapid experimentation with enterprise standards, documenting technical decisions, managing delivery commitments, and escalating material risks or dependencies early.
- Develop reusable prompts, agent instructions, workflows, connectors, templates, and solution patterns; maintain the associated documentation and inventory so approved capabilities can be discovered, governed, supported, and scaled across the organization.
- Collaborate with Information Systems (IS), Information Security, Legal, Privacy, Data, and business process owners to ensure solutions follow enterprise architecture, responsible AI, data protection, and access-control requirements, with clear business ownership, human oversight, production support, monitoring, and escalation responsibilities.
- Evaluate data, content, integration, and process readiness; design secure connections across systems such as Microsoft 365, Teams, SharePoint, CRM (Salesforce), ERP (SAP), service management (ServiceNow), and other enterprise platforms; identify dependencies; and recommend pragmatic remediation or phased delivery approaches.
- Build proofs of concept and minimum viable solutions, validate technical feasibility and business value, gather user feedback, iterate rapidly, and work with technical and business owners to harden successful pilots for secure, reliable, scalable, observable, maintainable, and supported production use, including documented architecture, testing, performance, continuity, and support requirements.
- Define and track adoption, quality, active usage, time and capacity recaptured, cycle-time reduction, risk, reuse, and business-value metrics; communicate outcomes, limitations, and lessons learned to business leaders and executive stakeholders.
- Enable users through demonstrations, office hours, documentation, training, community engagement, and practical guidance that builds AI fundamentals, use-case awareness, prompting skills, and safe adoption practices.
- Troubleshoot technical and operational issues, coordinate with internal teams and vendors, identify recurring user and platform needs, provide actionable feedback to technology owners, and continuously improve solution performance, reliability, usability, and maintainability.
- Stay current on emerging AI, agentic, automation, and Microsoft platform capabilities; inventory capabilities already licensed, evaluate vendor and architecture fit against consistent criteria, and recommend whether to extend an existing platform, buy a solution, build a custom capability, or engage an external partner.
- Embody and live our company Values.
- Ability to travel internationally as required (up to 15% of time).
QualificationsEducation ☒ Bachelor's degree required
Specific Area of Study: Computer Science, Information Systems, Data Science, Engineering, or a closely related technical field.
Experience ☒ 5+ years of relevant experience
Specific Related Experience: Five or more years of experience in software engineering, solutions engineering, technical consulting, solutions architecture, or a related field, including hands-on delivery of AI, data, integration, low-code, or automation solutions. Demonstrated experience working directly with business stakeholders from discovery and business-case development through architecture, prototyping, production deployment, adoption, and value measurement is required. Hands-on experience with at least one enterprise AI platform is required; experience with Microsoft 365 Copilot, Copilot Studio, Power Platform, Azure AI services, or comparable technologies is strongly preferred, along with experience evaluating whether to extend, buy, or build solutions.
Skills- Exceptional consulting, active-listening, facilitation, and relationship-building skills; able to establish trust, surface competing needs, and build shared ownership with business and technical stakeholders at all levels across functions.
- Strong business-process analysis and problem-framing skills, with the ability to translate ambiguous needs into clear use cases, requirements, experiments, solution options, delivery plans, and measurable success criteria.
- Hands-on knowledge of generative AI, prompt and context engineering, retrieval-augmented generation, agents and multi-agent patterns, workflow automation, APIs, integrations, and evaluation methods for grounding, accuracy, reliability, safety, latency, and cost.
- Demonstrated experience building enterprise solutions with Microsoft 365 Copilot, Microsoft 365 Copilot Chat, Copilot Studio, Power Automate, Power Apps, SharePoint, Teams, Microsoft Graph, Dataverse, Azure AI services, or related Microsoft technologies.
- Demonstrated ability to design, build, test, debug, deploy, and maintain solutions using Python and at least one enterprise application language such as JavaScript, TypeScript, or C#, together with SQL, REST APIs, source control, cloud services, and modern software-development practices.
- Ability to design secure, governed integrations between AI agents and enterprise tools, APIs, applications, and data sources, including appropriate authentication, authorization, identity, permissions, privacy, compliance, responsible AI, and human-in-the-loop controls.
- Strong written and verbal communication skills, including the ability to explain technical concepts, architectural trade-offs, risks, and recommendations to nontechnical audiences and executive stakeholders.
- Demonstrated change-management and user-enablement skills, including training, documentation, demonstrations, community engagement, and adoption support.
- Outcome orientation with experience defining value hypotheses and measuring adoption, efficiency, quality, risk reduction, reuse, and business impact.
- Preferred: experience delivering production AI solutions, agentic workflows, retrieval-augmented generation, custom copilots, Azure AI Foundry or Azure OpenAI solutions, data pipelines, enterprise integrations, DevOps and CI/CD practices, observability, automated testing, and secure cloud application development. Experience designing, deploying, or governing Model Context Protocol (MCP) servers and familiarity with Microsoft Work IQ, Microsoft IQ, or comparable enterprise intelligence, semantic-grounding, and agent-context capabilities are also preferred.
Physical DemandsThe physical requirements described here are representative of those that must be met by an employee to successfully perform the essential functions of this job.
- ☒ Sit; use hands to finger, handle or feel objects, tools, or controls.
- ☒ Stand; walk; reach with hands and arms; and stoop, kneel, crouch, or crawl.
- ☒ Other (please specify): Domestic & International travel (approx. 15%), including extended flights and work across multiple time zones.
