AI Solutions Engineer

Alliance Aviation Services • Dallas, TX

3d • Onsite

About The Position

Hillwood IT is seeking a hands-on AI Solutions Engineer to join our growing in-house IT team in Dallas, TX and help build the technical foundation for Hillwood's enterprise AI capability. This role is responsible for converting approved business use cases into secure, reliable, production-grade GenAI solutions, automations, agents, integrations, and RAG-enabled applications that deliver measurable business value. The AI Solutions Engineer will partner closely with AI Business Solutions Engineers, division stakeholders, IT architecture, security, data teams, and governance groups to transform approved AI opportunities into scalable production solutions. This is not a research-only or advisory role. Success is defined by delivering AI solutions that are technically sound, supportable, and trusted by business users while establishing reusable patterns that enable AI capabilities to scale across Hillwood. The ideal candidate is motivated by the opportunity to build more than isolated tools. This individual will help create the technical foundation, standards, and solution patterns that allow AI to become a trusted, repeatable, and high-value capability across the organization.

Requirements

• Ability to design, build, and support GenAI solutions, including LLM integration, prompt engineering, structured outputs, and Retrieval-Augmented Generation (RAG) pipelines.
• Strong hands-on engineering capability using Python, REST APIs, Azure services, workflow automation tools, and enterprise integration patterns.
• Ability to design and implement agent-based and multi-step workflows, including orchestration and execution of real business actions.
• Ability to build reliable AI systems with validation, testing, observability, error handling, security awareness, and production supportability.
• Ability to translate business-approved requirements into technical implementation plans, architecture diagrams, build tasks, and deployment plans.
• Demonstrated ability to apply delivery discipline, including pilot gate methodology, documentation standards, quality validation, and lifecycle governance.
• Ability to collaborate cross-functionally with business leaders, AI champions, governance bodies, IT architecture, security, and data teams to drive successful outcomes.
• Proficiency in Python for LLM integration, API development, automation scripting, data processing, and evaluation workflows.
• Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or related field.
• Demonstrated delivery of production-grade GenAI solutions used by real business users.
• Hands-on experience designing and building multi-step, agentic workflows using orchestration frameworks.
• Experience with at least one major LLM platform (Claude, OpenAI, Azure OpenAI, or equivalent), including prompt engineering, function calling, and structured outputs.
• Experience developing Retrieval-Augmented Generation (RAG) solutions and contextual intelligence pipelines.
• Experience building APIs, cloud functions, workflow automations, data integrations, or backend services in an enterprise environment.

Nice To Haves

• Azure platform experience, including Azure Functions, Logic Apps, Azure AI Studio, Azure OpenAI Service, Azure AI Search, or related services, preferred.
• Experience with Power Automate or similar low-code workflow tools, preferred.
• Experience with vector databases, document intelligence pipelines, or advanced RAG architectures, strongly preferred.
• Exposure to enterprise data platforms and business systems such as Databricks, Power BI, JDE, Yardi, Salesforce, SharePoint, or Medius, a plus.
• Familiarity with real estate, property management, financial services, lease management, AP automation, or property operations, a plus.
• Consulting, internal innovation, or client-facing delivery experience is helpful, but deep hands-on delivery ownership is more important for this technical role.

Responsibilities

• Partner with AI business solution leads to translate approved business requirements, success metrics, and pilot criteria into technical solution designs and solutions.
• Design and build production-grade GenAI applications, automations, agents, and RAG-enabled workflows for approved business use cases.
• Create technical designs suitable for Architecture Review Board (ARB), security, and production readiness review.
• Develop reusable solution patterns, templates, and implementation standards that can be applied across multiple use cases and divisions.
• Balance speed of delivery with reliability, maintainability, and enterprise supportability.
• Build, iterate, and deliver production-grade GenAI solutions for approved Horizon 1 use cases.
• Design and implement agentic workflows using orchestration frameworks and multi-step agents that perform real actions.
• Integrate AI solutions with Hillwood’s existing technology stack, including Claude API, ChatGPT, Copilot, Azure Functions, Power Automate, JDE, Yardi, Salesforce, SharePoint, Medius, Databricks, and other enterprise platforms.
• Develop APIs, Azure Functions, workflow automations, backend services, data connectors, and application components required to operationalize AI solutions.
• Own technical solution quality, including prompt engineering, structured outputs, output validation, error handling, evaluation, logging, monitoring, and reliability for business-critical use.
• Develop AI coding assistant support and CI/CD pipeline integrations for enterprise environments.
• Operate within Hillwood’s risk-tier governance framework, ensuring ARB review and lifecycle gates for Medium and High-risk solutions.
• Implement Retrieval-Augmented Generation (RAG) pipelines, document intelligence workflows, structured extraction workflows, and contextual intelligence patterns.
• Build and maintain reusable components for document parsing, chunking, metadata enrichment, embeddings, retrieval, citations, validation, and source traceability.
• Support the creation of technical standards for prompts, tools, agents, evaluators, test datasets, and deployment patterns.
• Partner with data teams to connect AI workflows to enterprise data platforms, reporting layers, and business systems.
• Support discovery, scoping, and prioritization by advising on technical feasibility, implementation complexity, dependencies, risks, and support needs.
• Support Steering Committee, division leadership, and ARB presentations by preparing technical architecture, demo environments, implementation status, risk considerations, and production readiness inputs.
• Partner with Division AI Champions and business stakeholders to ensure solutions are usable, explainable, and aligned to business workflows.
• Prepare or contribute to technical documentation, support readiness assessments, adoption materials, and scale recommendations.
• Communicate technical concepts clearly to non-technical stakeholders when needed, while partnering with AI business solution leads on executive framing and ROI narratives.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level