Job Description

We are Lennar 

Lennar is one of the nation's leading homebuilders, dedicated to making an impact and creating an extraordinary experience for their Homeowners, Communities, and Associates by building quality homes and providing exceptional customer service, giving back to the communities in which we work and live in, and fostering a culture of opportunity and growth for our Associates throughout their career. Lennar has been recognized as a Fortune 500® company and consistently ranked among the top homebuilders in the United States.

Join a Company that Empowers you to Build your Future

Lennar Technology Group (LTG) is building enterprise AI capabilities that directly accelerate the nation’s largest homebuilder. We are looking for a Principal Machine Learning Engineer / Senior Software Developer who brings deep expertise at the intersection of financial technologies and applied artificial intelligence to join our Applied AI & Solutions Design team.

In this role, you will architect and deliver production-grade ML systems that serve Finance, Accounting, Capital Markets, and Mortgage operations—working shoulder-to-shoulder with Senior Enterprise Architects, Senior Business Solutions Architects, and cross-functional stakeholders across the organization. You will regularly present strategy, progress, and technical recommendations to SVP-level and C-suite leadership, making this a high-visibility position with material impact on corporate decision-making.

The ideal candidate will combine strong ML/AI engineering skills with a proven track record in financial services, fintech, or corporate finance environments—and will bring the executive communication skills required to translate complex technical work into business outcomes for senior leadership audiences.

• A career with purpose.

• A career built on making dreams come true.

• A career built on building zero defect homes, cost management, and adherence to schedules.

Your Responsibilities on the Team 

Financial AI / ML Engineering

• Design, build, and deploy production ML models and pipelines for financial applications including forecasting (home starts, revenue, margin), anomaly detection, risk scoring, and portfolio analytics.
• Develop AI-driven solutions that integrate with core financial systems (ERP, GL, treasury, mortgage origination) to automate and enhance decision-making.
• Architect data pipelines and feature stores that ingest structured financial data (transactions, P&L, balance sheet, loan-level tapes) for model training and inference at enterprise scale.
• Implement model governance, versioning, explainability (SHAP, LIME), and auditability frameworks to satisfy internal compliance and regulatory requirements.

Enterprise AI Platform & Architecture

• Contribute to LTG’s enterprise AI platform roadmap spanning GenAI observability, Agent Registry, LLM model deployment, and AI governance.
• Build and operate multi-agent systems (AWS Bedrock, Strands/AgentCore, Anthropic APIs) integrated with enterprise tools (ServiceNow, Confluence, SharePoint, Microsoft Entra).
• Partner with Senior Enterprise Architects and Business Solutions Architects to ensure ML solutions align with Lennar’s technology standards, security posture, and cloud architecture.
• Evaluate and integrate third-party AI/ML platforms and observability tooling (e.g., Weights & Biases, Coralogix) into the production stack.

Executive Communication & Leadership Engagement

• Present technical strategy, project outcomes, and investment recommendations to SVP and C-suite leadership on a regular cadence.
• Translate complex ML and financial modeling concepts into clear, actionable business narratives for non-technical executives.
• Represent the Applied AI team in cross-functional steering committees, budget reviews, and strategic planning sessions with Finance, HR, IT, and Operations leadership.
• Author executive-ready documentation including business cases, architecture decision records, and compliance impact assessments.

Cross-Functional Collaboration

• Work closely with Finance, Accounting, Mortgage, and Capital Markets teams to identify high-value ML use cases and translate business requirements into technical specifications.
• Partner with the Technology Compliance team on AI governance, data privacy (PII handling in LLM traces), and regulatory alignment.
• Mentor engineers and analysts on ML best practices, financial domain knowledge, and production engineering standards.

Financial Technology & Domain Expertise

• 8+ years of professional software engineering or ML engineering experience, with at least 4 years focused on financial services, fintech, capital markets, mortgage technology, or corporate finance applications.
• Deep working knowledge of financial data structures, instruments, and processes (e.g., loan origination, underwriting models, financial forecasting, treasury operations, regulatory reporting).
• Demonstrated experience building ML models that consume financial data to drive business outcomes (e.g., credit risk, pricing optimization, fraud detection, demand forecasting, margin analysis).

Machine Learning & AI Engineering

• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost) with production deployment experience.
• Hands-on experience with LLMs, RAG architectures, vector databases, and agentic AI patterns (multi-agent orchestration, tool use, function calling).
• Strong background in cloud-native ML infrastructure (AWS SageMaker, Bedrock, Lambda, Step Functions; or Azure ML, OpenAI Service).
• Experience with ML observability, experiment tracking, model registry, and CI/CD for ML pipelines (MLflow, W&B, Kubeflow, or equivalent).

Executive Presence & Communication

• Proven track record of presenting technical work to SVP-level or C-suite audiences in prior roles; comfort operating in high-visibility, executive-facing settings.
• Ability to author polished executive summaries, business cases, and strategy documents that connect technical capabilities to business value.
• Experience reporting directly to or partnering closely with senior leadership (VP / SVP / C-suite) on technology strategy and investment decisions.

Requirements

Financial Technology & Domain Expertise

• 8+ years of professional software engineering or ML engineering experience, with at least 4 years focused on financial services, fintech, capital markets, mortgage technology, or corporate finance applications.
• Deep working knowledge of financial data structures, instruments, and processes (e.g., loan origination, underwriting models, financial forecasting, treasury operations, regulatory reporting).
• Demonstrated experience building ML models that consume financial data to drive business outcomes (e.g., credit risk, pricing optimization, fraud detection, demand forecasting, margin analysis).

Machine Learning & AI Engineering

• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost) with production deployment experience.
• Hands-on experience with LLMs, RAG architectures, vector databases, and agentic AI patterns (multi-agent orchestration, tool use, function calling).
• Strong background in cloud-native ML infrastructure (AWS SageMaker, Bedrock, Lambda, Step Functions; or Azure ML, OpenAI Service).
• Experience with ML observability, experiment tracking, model registry, and CI/CD for ML pipelines (MLflow, W&B, Kubeflow, or equivalent).

Executive Presence & Communication

• Proven track record of presenting technical work to SVP-level or C-suite audiences in prior roles; comfort operating in high-visibility, executive-facing settings.
• Ability to author polished executive summaries, business cases, and strategy documents that connect technical capabilities to business value.
• Experience reporting directly to or partnering closely with senior leadership (VP / SVP / C-suite) on technology strategy and investment decisions.

Education

• Bachelor’s degree in Computer Science, Financial Engineering, Applied Mathematics, Statistics, Economics, or a related quantitative discipline.
• Master’s degree or MBA with a quantitative or finance concentration is strongly preferred.
• Equivalent experience in financial technology or quantitative finance will be considered in lieu of advanced degree.

Construction, Homebuilding, or Adjacent Industry Experience

• Prior experience in homebuilding, real estate development, construction technology, property management, mortgage lending, or title/escrow operations.
• Familiarity with homebuilder business processes: land acquisition, entitlements, starts planning, purchasing, construction scheduling, closings, and warranty.
• Understanding of construction ERP systems (e.g., JD Edwards, SAP, BuildPro, Hyphen Solutions) and how financial data flows through homebuilding operations.
• Experience with real estate data platforms, MLS integrations, or housing market analytics.

Additional Technical Differentiators

• Experience with Model Context Protocol (MCP) integration, AWS AgentCore, or similar agentic AI orchestration frameworks.
• Background in NLP applied to document-heavy financial workflows (contracts, disclosures, compliance documents, call transcripts).
• Familiarity with AI governance frameworks, algorithmic bias assessment, and emerging AI regulations (Colorado AI Act, NYC Local Law 144, EU AI Act).
• Published research or patents in financial ML, NLP, or related fields.

Leadership & Strategic Contributions

• Experience standing up AI/ML functions or Centers of Excellence within large enterprises.
• History of vendor evaluation and platform selection for enterprise AI/ML tooling.
• Board-level, investor, or executive committee presentation experience.

You will work across the following technology landscape (not all-inclusive):

Category

Technologies

Cloud & Infra

AWS (Bedrock, SageMaker, Lambda, Step Functions, AgentCore, PrivateLink), Azure OpenAI Service

ML / AI

Python, PyTorch, TensorFlow, scikit-learn, XGBoost, LangChain, LlamaIndex, Anthropic APIs

Data & Analytics

Snowflake, Redshift, dbt, Spark, Pandas, SQL, feature stores

Agentic AI

Multi-agent orchestration (Strands/AgentCore), RAG, vector DBs (Pinecone, pgvector), MCP

Observability

Weights & Biases Weave, Coralogix, MLflow, CloudWatch

Enterprise Systems

ServiceNow, Confluence, SharePoint, Microsoft Entra, JD Edwards

DevOps / MLOps

Terraform, Docker, GitHub Actions, CI/CD, GitOps

• Be part of the AI transformation at one of America’s largest homebuilders with $35B+ in annual revenue.
• Join a small, high-impact Applied AI team with direct access to executive leadership and strategic decision-making.
• Work on production AI systems that affect real business outcomes—not just prototypes.
• Opportunity to shape AI governance, compliance, and platform standards at enterprise scale.
• Collaborative culture that values technical depth, intellectual honesty, and business impact over titles.

Life at Lennar

At Lennar, we are committed to fostering a supportive and enriching environment for our Associates, offering a comprehensive array of benefits designed to enhance their well-being and professional growth. Our Associates have access to robust health insurance plans, including Medical, Dental, and Vision coverage, ensuring their health needs are well taken care of. Our 401(k) Retirement Plan, complete with a $1 for $1 Company Match up to 5%, helps secure their financial future, while Paid Parental Leave and an Associate Assistance Plan provide essential support during life's critical moments. To further support our Associates, we provide an Education Assistance Program and up to $30,000 in Adoption Assistance, underscoring our commitment to their diverse needs and aspirations. From the moment of hire, they can enjoy up to three weeks of vacation annually, alongside generous Holiday, Sick Leave, and Personal Day policies. Additionally, we offer a New Hire Referral Bonus Program, significant Home Purchase Discounts, and unique opportunities such as the Everyone’s Included Day. At Lennar, we believe in investing in our Associates, empowering them to thrive both personally and professionally. Lennar Associates will have access to these benefits as outlined by Lennar’s policies and applicable plan terms. Visit Lennartotalrewards.com to view our suite of benefits.

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Lennar is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws.