Platform Engineer

• Own and evolve the financial data integration and ML classification platform
• Build, train, and deploy classification models served via Wallaroo to predict financial field/table mappings from document headers
• Extend BERT-based question-answering models for extracting structured data from free-text property descriptions
• Maintain and extend the configuration-driven pipeline orchestration system
• Match incoming files to processing pipelines, execute dynamic conditionals, and write standardized output to downstream templates
• Evolve the parsing library for complex Excel workbooks with nested headers, multi-tab structures, merged cells, and varied accounting system formats
• Improve prediction accuracy, expand audit logging, and ensure processing integrity across clients and document types
• Drive technical decisions on model-serving infrastructure, database schema design, and API integration patterns with RealPage's Data Management Gateway (DMG)
• Provide mentorship and technical guidance to one direct report

• Build internal platform tools and services, including self-service portals/workbenches, backend APIs using Python/FastAPI, automations, and CI/CD tooling
• Develop MCP/gateway integrations and AI-enabled automations and flows
• Reduce friction for teams adopting the platform
• Write and maintain Terraform; provision and configure platform resources across AWS and Azure
• Diagnose deployment, networking, endpoint, and configuration issues
• Partner with security and networking specialists
• Collaborate in standups, syncs, planning and project meetings
• Participate in design and architecture reviews, PR reviews, and code reviews
• Onboard new teams and translate ambiguous requirements into practical plans
• Challenge weak designs
• Help teams productionize models across SageMaker, Bedrock, Azure ML/AI Foundry, and Kubernetes, including hosting, inference, scaling, cost, and operational readiness
• Create documentation, onboarding guides, and reference examples
• Identify and implement process and platform improvements proactively

AI/ML Platform Engineer

• Build internal platform tools and services, including self-service portals/workbenches, backend APIs using Python/FastAPI, automations, and CI/CD tooling
• Develop MCP/gateway integrations and AI-enabled automations and flows
• Reduce friction for teams adopting the platform
• Write and maintain Terraform; provision and configure platform resources across AWS and Azure
• Diagnose deployment, networking, endpoint, and configuration issues
• Partner with security and networking specialists
• Participate in standups, syncs, planning and project meetings
• Conduct design and architecture reviews and regular PR/code reviews
• Onboard new teams and translate ambiguous requirements into practical plans
• Support productionization of models across SageMaker, Bedrock, Azure ML/AI Foundry, and Kubernetes, including hosting, inference, scaling, cost, and operational readiness
• Create documentation, onboarding guides, and reference examples
• Identify and implement process and platform improvements proactively

• Build and operate secure, scalable microservice applications on AWS and Kubernetes
• Own reliability and observability to keep the platform stable under load
• Develop and integrate AI and agentic capabilities, including LLM integration, retrieval augmented generation, tool and function calling, and agentic workflows
• Apply security-first practices across application, API, container, identity, and data security
• Automate testing, delivery, and monitoring through modern DevSecOps practices
• Troubleshoot complex production issues through resolution
• Contribute to engineering practices and standards
• Deliver reliable production services and usable AI features for customers

Software Microservices Platform Engineering Lead, AI – Agentic AI

• Own integrated technical program plans including roadmap, milestones, critical path, and delivery execution for broadband device programs
• Lead cross-functional workstreams across hardware, software, validation, security, manufacturing, and launch readiness activities
• Establish and govern program stage gates including Architecture Review, Engineering Validation, Design Verification Testing, Production Validation Testing, and launch readiness reviews
• Manage vendor and partner execution, including statements of work, deliverables, schedules, change control, and integration activities
• Drive engineering execution through release planning, risk management, defect resolution, quality governance, and executive-level status reporting
• Lead launch readiness, field trial execution, post-launch support, and continuous product improvements through telemetry-driven insights
• Transform strategic business objectives into broadband device solutions across consumer and enterprise markets
• Provide technical leadership, influence executive decisions through data-driven recommendations, establish engineering standards, and mentor teams across multiple programs

Platform Engineer jobs in Texas