AI Embedded Business Automation Engineer

Overview

When you join Hines, you will embark on a career journey fueled by vision and guided by leaders who set the standards of our industry. Our legacy is rooted in innovation and excellence, earning us a spot on Fast Company’s esteemed annual list of the World’s Most Innovative Companies, as well as recognition as one of U.S. News & World Report’s Best Companies to Work For in 2024. Discover endless opportunities to grow and make your mark at Hines.

The AI Embedded Business Automation Engineer will work within functional departments across the organization to uncover opportunities where AI, automation, and better system design can meaningfully improve business operations. This role will work directly with the business teams to understand how work happens today, pinpoint manual handoffs, rework, delays, and exception-heavy processes, and then design, prototype, and deliver technical solutions that make day-to-day work faster, smarter, and more scalable.

The role requires the ability to independently translate complex business needs, strategic objectives, and operational challenges into actionable technical requirements, architectural designs, and scalable AI and data solutions. Equally important is the ability to translate sophisticated technical concepts, architectural decisions, and solution limitations into clear, concise, business-oriented recommendations that enable informed executive decision-making.

• Independently engage business leaders to understand strategic priorities, identify opportunities, define requirements, and translate business needs into practical, scalable AI, data, and technology solutions.
• Develop and deliver compelling presentations, architectural recommendations, and strategic proposals to senior leadership, effectively communicating technical concepts, business implications, risks, trade-offs, and expected outcomes to both technical and nontechnical audiences.
• Co-design AI-enabled process improvements with SMEs, translating operational challenges into practical workflows that improve efficiency, accuracy, user experience, and business capacity.
• Translate business requirements into clear technical specifications, solution designs, implementation plans, and delivery milestones, then build agentic and automation solutions end-to-end in partnership with business teams, teammates, and senior engineers.
• Rapidly prototype, test, and iterate on AI-driven automations, assistants, agents, and workflow solutions using Python, LLM APIs, RAG patterns, agent frameworks, workflow orchestration, and enterprise platforms.
• Develop and maintain integrations with enterprise systems such as SharePoint, Teams, Outlook, ERP platforms, Salesforce, internal applications, APIs, and data sources to enable end-to-end intelligent workflows.
• Design and implement trustworthy AI solution components, including prompt orchestration, RAG pipelines, document ingestion, vector search, backend services, automation logic, data pipelines, models, and secure access patterns.
• Support adoption through SME enablement, practical training, feedback loops, and usage-based refinement so business teams actively shape and sustain the workflows being introduced.
• Embed security, privacy, compliance, and responsible AI controls throughout the solution lifecycle, including data classification, least-privilege access, secrets management, auditability, and safe data handling.
• Remain accountable for production quality by deploying, monitoring, troubleshooting, optimizing, and continuously improving AI and automation solutions with a focus on reliability, performance, security, governance, cost management, and real-world usage.
• Work cross-functionally with engineering, product, security, legal, and business teams to move solutions from concept through pilot, production launch, adoption, support, and ongoing enhancement.
• Document solution architecture, implementation decisions, support procedures, runbooks, and best practices, and create repeatable agent, automation, integration, and data patterns that scale across functions while aligning with IT governance and architecture standards.
• Define success metrics and measure solution impact, including cycle-time reduction, quality improvements, adoption, reliability, and unlocked business capacity.
• Communicate project progress, risks, decisions, and results to technical and nontechnical audiences, tailoring the level of detail to the audience.
• Build alignment across business and technology teams, facilitate decisions, and set clear expectations for scope, timing, ownership, and adoption.
• Own AI and automation initiatives from stakeholder discovery through launch, adoption, and measurement of business impact.
• Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, Data Science, Mathematics, or a related field; equivalent practical experience may also be considered.
• 5-7+ years of experience in software engineering, automation engineering, cloud engineering, data engineering, integration development, or related technical roles, including experience delivering AI or Generative AI solutions in a business environment.Experience building workflow automations, APIs, integrations, copilots, assistants, or AI-enabled business applications using Microsoft, Azure, OpenAI, ChatGPT Enterprise, or comparable enterprise platforms.
• Experience supporting production systems, partnering with cross-functional stakeholders, and translating business needs into secure, scalable technical solutions.
• Strong product judgment, communication skills, and delivery orientation, with the ability to release useful increments quickly, recognize when a more durable solution is needed, and write specs, docs, and updates that are clear without additional explanation.
• Demonstrated ability to deliver reliable code, services, integrations, or automations used in day-to-day business operations.
• Demonstrated ability to independently lead AI and data architecture decisions, establish and implement architectural standards, and own complex technical design and delivery with limited developmental support.
• Required coding proficiency in Python, with the ability to write clean, tested, maintainable code and contribute effectively to shared production codebases.
• Hands-on experience applying LLMs and Generative AI to real business problems, including prompt engineering, LLM APIs, retrieval-augmented generation, AI-enabled workflows, prototypes, assistants, or agents.
• Experience using AI-assisted development tools and building tool-using workflows or custom agents that leverage MCP or similar agent integration patterns and connect securely to enterprise systems, APIs, data sources, and business applications.
• Demonstrated ability to turn business problems into technical specifications, solution designs, implementation plans, and working software that can be explained clearly to non-technical partners.
• Working knowledge across several core enterprise engineering areas, including cloud infrastructure, data engineering, SQL, pipelines, integration patterns, automation tooling, IAM, APIs, and enterprise application development.
• Familiarity with information security fundamentals, including authentication, authorization, encryption, secrets management, safe data practices, least-privilege access, auditability, andresponsible AI guardrails.
• Strong business acumen and consultative skills, with the ability to assess business challenges, evaluate solution alternatives, and articulate the strategic and financial implications of technical decisions.

• Experience with Microsoft and OpenAI tools such as Azure OpenAI Service, OpenAI APIs, ChatGPT Enterprise, Microsoft Copilot Studio, Azure AI Foundry, Semantic Kernel, OpenAI Agent SDK, Power Platform, or comparable platforms.
• Familiarity with advanced agent, retrieval, and orchestration patterns, including vector search, iPaaS tools, LangGraph, LangChain, LlamaIndex, or similar frameworks, is a plus.
• Familiarity with TypeScript, JavaScript, Go, or Java is a plus.
• Experience designing AI-enabled business process automations across functions such as finance, legal, operations, or other enterprise teams.

The successful candidate will

• Build trust with functional SMEs by understanding their workflows in depth and turning business challenges into practical AI-enabled solutions.
• Deliver secure, scalable, production-ready AI and automation solutions that improve how work is performed across business functions.
• Move quickly from discovery to prototype to production while balancing speed, quality, governance, reliability, performance, and cost efficiency.
• Drive measurable impact through adoption, cycle-time reduction, quality improvement, reusable delivery patterns, and additional business capacity.

Closing

At Hines, we believe the built world is ultimately about people. As one of the world’s largest privately held real assets firms, we bring nearly seven decades of investment, development, and management experience to work that shapes cities and communities around the world.

Our people make that possible. Across 29 countries, more than 4,600 colleagues bring different perspectives and expertise to Hines, with opportunities to take on meaningful responsibility, learn from leaders across the business, and build a career with room to evolve. We support that journey through professional development, competitive rewards, comprehensive benefits, and a culture grounded in trust and high standards.

Hines is proud to be named to Fast Company’s annual list of the World’s Most Innovative Companies for 2024.

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