Forward Deployment Engineer

Position: Forward Deployment Engineer
Location: Houston, TX (On-site)
Duration: Long term

Key Responsibilities
AI Agent Development
Build enterprise AI agents using Microsoft Copilot Studio and Microsoft Foundry.
Develop custom enterprise actions, tools, connectors, APIs, and workflow automations for AI agents.
Design and implement agent orchestration, grounding, tool calling, and multi-agent/domain-agent integrations.
Experience building evaluation harnesses, testing models, optimizing prompts, and fine-tuning models where appropriate.
Implement RAG pipelines, including embeddings, chunking strategies, indexing, grounding, vector search, and retrieval optimization.
Create reusable agent components, templates, prompts, actions, and integration patterns for rapid deployment across departments.
Conduct testing, debugging, evaluation, optimization, versioning, monitoring, and maintain an enterprise registry of agents.
Implement appropriate safeguards, access controls, auditability, and responsible AI practices for production agents.
Develop enterprise solutions using Power Apps, Power Automate, Power Pages, Dataverse, Copilot Studio, and Power Platform connectors.
Develop cloud flows, approval workflows, event-driven automation, scheduled processes, and system-to-system integrations using Power Automate.
Integrate Power Platform solutions with Copilot Studio agents and enterprise AI services.

Enterprise Integrations
Integrate agents and Power Platform solutions with SAP, SQL Server, SharePoint, Salesforce, ServiceNow, and other platforms within the AACo ecosystem.
Build and maintain REST APIs, custom connectors, integration services, and automation workflows.
Integrate enterprise applications through approved integration platforms and API layers where appropriate.
Ensure secure authentication, authorization, identity management, secrets management, and data access across systems.
Design integrations that support enterprise scalability, reliability, observability, and maintainability.

Data Engineering & AI Pipelines
Prepare structured and unstructured enterprise data for AI agent consumption.
Design ingestion, transformation, indexing, and retrieval pipelines for enterprise knowledge.
Manage vector and retrieval technologies such as Azure AI Search, SQL Server, and Redis, based on solution requirements.
Implement RAG quality controls, retrieval evaluation, grounding validation, and optimization.
Implement data governance, lineage, cataloguing, retention, access controls, and security requirements.
Ensure agents and Power Platform solutions respect source-system permissions and enterprise data boundaries.

Forward Deployment & Business Engagement
Embed directly with departments and business units to understand workflows, identify pain points, and discover opportunities for AI and automation.
Rapidly prototype, test, and deploy agents, Power Apps, workflows, integrations, and automation solutions in short iteration cycles.
Gather business requirements and translate them into technical architecture, user stories, development tasks, integrations, and deployable solutions.
Conduct workshops and proof-of-concepts with business teams before scaling successful solutions.
Work closely with application owners, security, infrastructure, architecture, data, and business teams to move prototypes into production.
Identify opportunities where a Copilot agent, Power App, Power Automate workflow, traditional API/application, or combination of these technologies is the most appropriate solution.
Develop reusable patterns that allow successful departmental solutions to be scaled across the enterprise.

DevOps, Governance & Operations
Implement CI/CD and ALM practices for AI agents and Power Platform solutions.
Maintain source control, deployment pipelines, environment configurations, solution versioning, and release documentation.
Establish monitoring, logging, telemetry, and operational support for deployed agents and applications.
Monitor AI usage, model/token consumption, API utilization, Power Platform capacity, performance, and operational cost.
Follow enterprise cybersecurity, data privacy, compliance, change-management, and architecture standards.
Maintain technical documentation, solution architecture, integration specifications, and support procedures.