Local, and Tribal governments. Emphasis is placed on configuration-first development,
CI/CD, data/content ingestion pipelines, and ongoing operations to ensure reliable
production performance.
This position partners closely with technical teams and federal stakeholders to implement
scalable low-code solutions, establish repeatable delivery patterns, and support the
knowledge/content lifecycle that powers AI experiences (e.g., ingestion, validation, refresh,
governance, and monitoring). Traditional, heavy machine learning model development is
not a primary expectation for this role, though limited support may be required as future
mission use cases evolve.
U.S. Citizenship is required, along with the ability to obtain and maintain a federal Public
Trust investigation. This position is fully remote within the United States.
Core Responsibilities
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Enable and deliver low-code AI solutions using Microsoft Power Platform and
Copilot Studio to support enterprise mission needs.
Configure, integrate, and operationalize AI experiences, including connectors,
workflows, approvals, and automation patterns that support secure enterprise
adoption.
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Support cloud delivery within Microsoft’s specialized government cloud
environment (Government Cloud Computing/Government Community Cloud),
ensuring solutions align with federal security, compliance, and governance
requirements.
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Implement and maintain CI/CD processes for Power Platform/Copilot solutions
(solution packaging, environment promotions, release management, and
deployment automation).
Build and support data/content ingestion pipelines that prepare and maintain
knowledge sources for AI experiences (knowledge lifecycle management,
validation, refresh schedules, and quality checks).
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Deploy, monitor, and optimize low-code AI solutions in production, including
telemetry, alerting, performance monitoring, and incident response support.
Partner with Data Engineers and platform teams to ensure content and data are
structured, accessible, and maintained for AI-enabled experiences (without
requiring heavy feature engineering or predictive modeling).
Use Python or lightweight scripting only as needed for function calls, integration
edge cases, automation gaps, or specialized operational support.
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