Forward Deployed Engineer — Applied AI

HomeSmart Services • Scottsdale, AZ

5d • Hybrid

About The Position

HomeSmart is seeking a hands-on applied AI engineer to work directly with internal teams and affiliated businesses. The role identifies meaningful business problems and builds practical solutions, from initial prototype through production and ongoing improvement. Some projects have a defined scope, while others require investigating workflows and defining the problem. This individual-contributor role partners with engineering, data science, and infrastructure teams. Applicants may come from data science, applied AI/ML engineering, or full-stack development; prior Forward Deployed Engineer experience is not required.

The engineer will work with business teams to understand workflows, identify opportunities, and define success measures. They will build and deploy production-ready applications, APIs, integrations, AI-enabled workflows, and automation; develop reliable data pipelines and shared data models, including a business data ontology; and collaborate on machine-learning architecture, training and inference pipelines, testing, evaluation, troubleshooting, and performance improvements.

The role involves selecting an appropriate approach for each problem—AI/ML, deterministic logic, or conventional software—based on accuracy, latency, cost, and control. Solutions should incorporate security, access controls, traceability, error handling, testing, and human review, while protecting sensitive data and credentials. The engineer will monitor adoption, quality, time savings, and operating costs, and improve and maintain solutions after launch.

The position offers the opportunity to shape how a real estate business operates, working closely with users, stakeholders, and technical colleagues to build solutions that improve workflows and can become shared organizational capabilities. HomeSmart describes its approach as hybrid, combining collaboration in Scottsdale with focused engineering time.

Requirements

• Experience building software or AI applications and ability to explain contributions and technical tradeoffs.
• Strong Python skills.
• Working knowledge of SQL, APIs, software engineering fundamentals, version control, code review, and testing.
• Experience building with language models and evaluating their capabilities, limitations, and production performance.
• Comfort using AI development tools such as Claude Code, Codex, or Cursor, and ability to debug, validate, and improve generated code.
• Sound security judgment around permissions, data integrity, sensitive information, and production credentials.
• Clear communication, curiosity, initiative, and ability to work through ambiguity with technical and nontechnical partners.

Nice To Haves

• Experience with large-scale data systems, cloud infrastructure, deployment automation, machine learning, AI agents, retrieval, document understanding, workflow systems, semantic models, or ontologies.
• Experience with LangChain, LangGraph, or other orchestration tools.
• Examples of work such as a GitHub profile, portfolio, or project links; public code is not required.
• Demonstrated ability, sound judgment, and willingness to learn; professional work, independent projects, open source, and self-built products are all considered.

Responsibilities

• Work with business teams to understand workflows, identify opportunities, and define success measures.
• Build and deploy production-ready applications, APIs, integrations, AI-enabled workflows, and automation.
• Develop reliable data pipelines and shared data models, including a business data ontology connecting people, activities, documents, and relationships across systems.
• Collaborate on machine-learning architecture, training and inference pipelines, testing, and evaluation; troubleshoot issues and improve performance.
• Select an approach for each problem—AI/ML, deterministic logic, or conventional software—based on accuracy, latency, cost, and control.
• Build in security, access controls, traceability, error handling, testing, and human review; protect sensitive data and credentials.
• Monitor adoption, quality, time savings, and operating costs, then improve and maintain solutions after launch.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed