Forward Deployed Engineer — Applied AI

HomeSmart Services • Scottsdale, AZ

4d • 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 clear scope, while others require investigating workflows and defining the problem. This is an individual-contributor position that partners with engineering, data science, and infrastructure teams. HomeSmart welcomes data scientists, applied AI/ML engineers, and full-stack developers with strong engineering skills; prior Forward Deployed Engineer experience is not required.

The position offers the opportunity to help shape how a real estate business operates by working closely with users, stakeholders, and experienced technical colleagues. Solutions may improve individual workflows or become shared capabilities across the organization. HomeSmart's hybrid approach combines collaboration in Scottsdale with focused engineering time.

Requirements

• Experience building software or AI applications, with the ability to explain personal 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.
• Familiarity with LangChain, LangGraph, or other orchestration tools.
• A specific degree or set number of years of experience is not required; demonstrated ability, sound judgment, and willingness to learn are valued.
• Professional work, independent projects, open source, and self-built products all count as relevant experience.

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.
• Choose an appropriate 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