generative ai architect

GenAI Architect

Location Wichita KS, Dallas TX (Hybrid)

Contract to Hire

About the Role

We are seeking a GenAI Architect to define and lead the end-to-end architecture for intelligent, agent-based solutions that transform field service operations. This role will focus on designing scalable, secure, and production-grade AI systems leveraging Azure OpenAI Service to enable automation, real-time decision-making, and enhanced technician productivity.You will act as the technical authority for GenAI architecture, driving innovation while ensuring alignment with enterprise architecture standards.

Key Responsibilities

Architecture & DesignDefine the end-to-end architecture for GenAI-powered agent ecosystems using Azure OpenAI Service and the broader Microsoft Azure stack.Design scalable multi-agent frameworks, including orchestration, tool usage, planning, and memory management.Establish patterns for Retrieval-Augmented Generation (RAG), semantic search, and knowledge grounding.Architect integrations with enterprise platforms (Field Service Management systems, CRM, ERP, IoT platforms).Agent & AI Strategy

Define agent design principles (autonomous vs assistive agents, copilots, workflow agents).Select and standardize tools/frameworks (e.g., Semantic Kernel, LangChain, custom orchestrators).Design prompt engineering, evaluation frameworks, and feedback loops for continuous improvement.Drive AI solution standardization and reusable accelerators.Governance, Security & Responsible AIEstablish guardrails for responsible AI usage (bias mitigation, explainability, auditability).Ensure compliance with enterprise security, privacy, and regulatory requirements.Design monitoring, logging, and observability for AI systems.Performance & OptimizationArchitect for scalability, reliability, latency, and cost optimization of LLM workloads.Define strategies for model selection, fine-tuning, embeddings, and caching.Leadership & CollaborationPartner with business stakeholders to translate field service transformation goals into AI architecture.Provide technical leadership to engineers, data scientists, and program teams.Review designs, guide implementation, and ensure adherence to architectural standards.

Key Use Cases (Field Service Transformation)

AI copilots for field technicians (mobile-first assistance) Intelligent diagnostics and troubleshooting agentsAutomated work order summarization and recommendationsKnowledge retrieval from manuals, service history, and IoT signalsPredictive and prescriptive maintenance insights

Qualifications & Experience

Bachelor’s or Master’s degree in Computer Science, AI, Engineering, or related field.0–15+ years of experience in software engineering/architecture, with 5+ years in AI/ML systems.Proven experience designing enterprise-grade solutions using Azure OpenAI Service.Strong expertise in LLM architectures, including RAG, embeddings, vector databases, and agent frameworks.Hands-on experience with Azure services (Azure AI Search, Functions, Kubernetes, API Management, etc.).Experience integrating AI solutions with enterprise systems (CRM, FSM, ERP, IoT).Strong understanding of microservices, APIs, and cloud-native design patterns.

Key Competencies

Enterprise & solution architectureGenAI / LLM system designMulti-agent orchestrationCloud architecture (Azure-first)Security, governance & complianceStakeholder influence and technical leadership

Nice to Have

Experience with field service platforms (e.g., Dynamics 365 Field Service, ServiceNow FSM)Exposure to IoT/edge integrations in service operationsAzure AI / Cloud Architect certificationsExperience building reusable AI platforms or internal developer frameworks