Forward Deployment Engineer - Onsite(Houston,TX)

Title:  Forward Deployment Engineer

Location: Houston, TX (On-site)

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.