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Forward Deployment Engineer - Onsite(Houston,TX)

Zeforge LLCHouston, TX🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeOn Site
LocationHouston, TX, United States
SQLRedisGenerative AIRESTAzureSQL ServerSharePointCI/CDRAG

Job description

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.

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