Build and operate the AI platform that powers every agent at Polygon Labs, including agent runtime, MCP servers, guardrails, evaluations, observability, and spend tracking.
Responsibilities
Move agentic workflows into production, taking prototypes to robust systems for real users and owners
Build and manage MCP servers, including system design, hosting, security, authentication, and connector inventory
Develop autonomous agents that act and plan across tools through trust stages
Embed guardrails into the platform, providing each agent its own identity, scoped credentials, audit logs, CI checks, approval gates, allowlists, and least-privilege access
Build evaluation frameworks so every agent releases with quality metrics tied to business outcomes
We are seeking a highly skilled Data Engineer with a strong background in AI/ML Engineering to join our dynamic team in Plano, Texas. The ideal candidate will have 7-10 years of experience in data engineering, with a proven track record of designing and implementing data pipelines and architectures that support advanced analytics and machine learning initiatives.
Responsibilities
Design, develop, and maintain scalable data pipelines and architectures to support AI/ML applications.
Collaborate with data scientists to understand data requirements and ensure data availability for machine learning models.
Implement ETL processes to extract, transform, and load data from various sources into data warehouses and lakes.
Optimize data storage and retrieval processes for performance and efficiency.
Monitor and troubleshoot data pipeline performance and reliability.
This role is responsible for building and delivering a comprehensive reporting layer for Talent Acquisition, transforming raw data into actionable insights through automated dashboards. The specialist will own the entire data lifecycle from ingestion to visualization, ensuring scalability, data integrity, and user adoption of the reporting solutions. Success in this role will involve establishing a robust data foundation that empowers leadership with timely and accurate analytics for strategic decision-making.
Compensation
$60-65/hr-W2
Responsibilities
Establish and manage data connections from source systems to a cloud data warehouse.
Develop and maintain automated ELT pipelines for data ingestion and transformation.
Design and implement a dimensional data model tailored for recruiting analytics.
Create a suite of Power BI dashboards for talent acquisition performance monitoring.
Produce thorough documentation for the data architecture and reporting solutions.
Design, build and support the Oracle 19c database for a platform that aggregates retirement, health savings and stock plan data. This role will own the logical and physical data models, table creation scripts and database deployments across environments.
Compensation
The starting pay range for this role is $88.hour.
Responsibilities
Designing and tuning database structures
Maintaining database availability and security
Supporting repeatable deployments with reviewed scripts and rollback plans
Partnering with and mentoring ETL and Java developers on data modeling, SQL and database standards
Own strategy and the roadmap across core platform services, the data platform, and customer-facing data products to make the platform a unified system for every district.
Responsibilities
Set the strategy and roadmap across platform services, the data platform and data products.
Define and hold SLOs for SSO, SIS integrations and data acquisition.
Own SIS integrations and data acquisition so rostering data arrives reliably from every district.
Define what each pipeline layer delivers, from raw ingestion to curated data, and set data quality standards with the Data team.
Own shared metrics and data models, so terms like "active student" and "screen time" mean the same thing in every product.
The Principal Software Engineer will own the technical architecture of the operating system for Valar—the telemetry systems that capture every second of reactor and fuel test data, the streaming backbone that moves it, the simulation platforms our reactor engineers design with, and the enterprise systems that run the company.
Locations (2)
Torrance, California, United States
Orangeville, Utah, United States
Compensation
$195,000—$270,000 USD
Responsibilities
Own the end-to-end architecture of Valar's software platform across telemetry, streaming, simulation, and enterprise systems, and make the build-versus-buy calls that shape it for the next decade.
Design and build high-volume telemetry ingestion for reactor test stands, fuel manufacturing, and instrumentation—high-rate time-series at scale, with source timestamps, units, quality, and ordering preserved end to end.
Architect the streaming backbone that carries operational data to analytics, simulation, monitoring, and enterprise consumers, and engineer it for throughput, backpressure, replay, and recovery.
Principal Technical Product Manager, AI Growth Systems
Lead the design and implementation of an AI-driven customer journey system for high‑net‑worth real estate buyers, owning system architecture, AI agent behavior, and growth outcomes.
Compensation
Around $200,000- $225,000k depending on location and experience with equity (RSU's)
Responsibilities
Own system‑level design for new leads, dormant leads, and stalled buyers
Design customer intelligence layer and next‑best‑action logic
Define agent behavior, prompts, and tool orchestration
Shape technical design with engineering and review implementation
Set roadmap priorities across site, email, messaging, CRM, and sales handoffs
Requirements
Nice to have: Experience with high‑value purchases such as real estate, luxury, or financial services
Build and maintain data sources that power decision making, unifying fragmented data pipelines, building robust data models, and ensuring reliable data lineage across multiple product areas.
Responsibilities
Architect and implement scalable, reliable, and secure data pipelines and infrastructure to support analytics, reporting, and business operations
Design and enforce data modeling standards, data lineage, and governance frameworks that ensure consistency, re-usability, and quality across systems
Lead design and code reviews, driving engineering best practices across data development, documentation, testing, and monitoring
Build data platforms and frameworks that support both batch and real-time processing, enabling flexible, efficient analytics at scale
Implement secure and compliant data solutions that meet internal and external regulatory requirements (e.g., GDPR)
Support the simulation and modeling platform: Campaign management, compute scheduling, and reproducible, traceable results engineers can defend to regulators.
Architect and build full-stack services and web interfaces that engineers, operators, and technicians use daily, and integrate the commercial systems the company runs on (PLM, ERP, MES, document and records management) over REST, GraphQL, and event-driven interfaces.
Requirements
Bachelor's degree in computer science, engineering, mathematics, or a scientific discipline, or equivalent professional experience
Nice to have: Industrial data sources and protocols (historians, OPC UA, MQTT, Modbus)
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