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Senior Workforce AI Solutions Engineer

Xactware
Jersey City, USA
Full-time
Senior
Remote
Discovered 1 weeks ago
azureazure-functions

Full Job Posting

Required Qualifications

  • Experience in solution architecture, software engineering, automation, cloud engineering, application integration, or a related technology discipline.
  • Demonstrated experience delivering business-facing technical solutions from requirements through implementation.
  • Hands-on experience with one or more enterprise AI platforms such as Microsoft Copilot, Copilot Studio, Claude, ChatGPT Enterprise, or comparable technologies.
  • Experience working with APIs, SDKs, integrations, automation technologies, and structured or unstructured enterprise data sources.
  • Working knowledge of enterprise identity, authentication, authorization, and secure integration patterns.
  • Ability to build through both low-code and pro-code approaches and to select the appropriate method for the request.
  • Strong analytical, consulting, documentation, troubleshooting, and stakeholder communication skills.
  • Ability to manage multiple requests, balance business urgency with technical risk, and drive work to completion.

Preferred Qualifications

  • Experience building custom agents, AI assistants, agent actions, and multi-step AI workflows.
  • Experience developing MCP servers, custom skills, plugins, connectors, or similar extensibility components.
  • Experience with Microsoft Graph, REST APIs, Azure Functions, Logic Apps, Power Automate, GitHub, Visual Studio, or Visual Studio Code.
  • Knowledge of retrieval-augmented generation, enterprise search, grounding, vector search, and knowledge-management patterns.
  • Knowledge of responsible AI, data protection, security, compliance, auditability, and AI governance practices.
  • Experience identifying and measuring productivity, process, service-quality, or business-value improvements.
  • Success Measures
  • Timely movement of qualified requests from intake through delivery or an agreed disposition.
  • Business requester satisfaction and adoption of delivered solutions.
  • Demonstrated productivity, quality, service, or process improvements from implemented solutions.
  • Creation and reuse of standard agents, skills, MCP components, connectors, and solution patterns.
  • Reliable, secure, supportable solutions that comply with enterprise governance and architecture requirements.
  • Clear documentation, ownership, and lifecycle management for solutions placed into use.
  • Candidate Profile
  • The successful candidate combines curiosity about emerging AI capabilities with disciplined enterprise engineering. They can move comfortably between a business process conversation and a technical design discussion, explain tradeoffs clearly, build practical solutions, and recognize when a request should be simplified, escalated, or redirected. They are accountable for outcomes, thoughtful about risk, and motivated by improving how employees work.
  • #LI-LM03 #LI-Remote

Responsibilities

  • Purpose of the Role
  • Accelerate measurable business value from enterprise workforce AI investments.
  • Design and deliver AI-powered solutions that improve productivity, reduce manual effort, and simplify business processes.
  • Act as a technical advisor and solution architect for workforce AI technologies.
  • Establish reusable agents, skills, integrations, MCP components, and solution patterns that can be leveraged across the organization.
  • Drive responsible AI adoption while meeting enterprise security, governance, privacy, and compliance requirements.
  • Lead and coordinate delivery activities with the coworker supporting each request, including work allocation, technical direction, issue resolution, and completion accountability.
  • Manage and prioritize a queue of qualified AI solution requests received from business units across the company.
  • Partner with the intake and triage function to confirm scope, readiness, ownership, dependencies, and the appropriate delivery path, then lead execution with the coworker assigned to support delivery.
  • Work directly with requesters to understand business processes, desired outcomes, data needs, risks, and success measures.
  • Translate business requirements into practical AI solutions using approved platforms and technologies.
  • Estimate effort, communicate delivery expectations, document decisions, and maintain visibility into request status and outcomes.
  • Provide appropriate implementation documentation, knowledge transfer, and transition to an ongoing support model.
  • Design AI-enabled workflows, agents, automations, and business process improvements.
  • Select the appropriate platform and implementation approach based on business needs, technical fit, security, maintainability, and cost.
  • Build solutions through simple builder experiences, low-code platforms, and pro-code development using Visual Studio or Visual Studio Code when needed.
  • Create reusable design patterns, templates, components, and engineering standards that improve delivery speed and consistency.
  • Evaluate scalability, observability, supportability, and lifecycle requirements before production use.
  • Build and maintain purpose-specific AI agents, actions, prompts, workflows, and orchestration logic.
  • Develop custom skills and Model Context Protocol (MCP) servers or integrations when platform-native capabilities are insufficient.
  • Extend AI platforms using APIs, SDKs, custom connectors, functions, and other approved integration methods.
  • Apply software development practices such as source control, testing, documentation, release management, and reusable code design.
  • Design secure connections between workforce AI platforms and enterprise data sources, knowledge repositories, business applications, and external functions.
  • Understand and apply modern authentication and authorization patterns, including OAuth, Microsoft Entra ID, application registrations, service principals, managed identities, delegated access, and API-based credentials.
  • Partner with application owners, data owners, security, privacy, architecture, and identity teams to establish approved access patterns.
  • Ensure solutions follow least-privilege principles and protect enterprise data throughout retrieval, processing, storage, and output.
  • Maintain strong working knowledge of Microsoft Copilot, Copilot Studio, Claude, ChatGPT Enterprise, related APIs, and emerging enterprise AI capabilities.
  • Understand the strengths, limitations, licensing considerations, and integration options of each platform.
  • Evaluate new capabilities and identify where they can improve solution quality, reduce development effort, or expand supported use cases.
  • Share lessons learned and reusable practices with AI enablement, platform, security, and engineering teams.

Key Responsibilities

  • Request Queue Management and Solution Delivery
  • AI Solution Architecture and Engineering
  • Agent, Skill, and MCP Development
  • Integration, Data, and Authentication
  • Platform Expertise and Continuous Improvement

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