Senior Principal Software Engineer

Procore Technologies•Austin, TX

10d

About The Position

We are seeking a Senior Principal Software Engineer to serve as a senior technical leader responsible for defining and executing the long term technical strategy for backend and AI services that power data applications and production grade data platform capabilities. This role will directly shape how we use data and AI to improve customer and project health visibility, and drive long term customer value through increased engagement, adoption, and retention. You will shape architectural standards, platform evolution, AI enablement, and modern development practices. As the company accelerates investment in AI, you will play a pivotal role in defining how AI capabilities are designed, governed, scaled, and embedded into core products and internal platforms in a secure, reliable, and cost effective manner. You will work from a clear vision of the desired future state and methodically guide systems toward that outcome through deliberate architectural decisions and pragmatic, iterative execution. This role blends strategic leadership with hands-on impact. You will contribute high leverage production code, establish cross cutting architectural patterns, eliminate ambiguity in complex initiatives, and elevate engineering standards across teams.

Requirements

15+ years of software engineering experience, including deep expertise in backend system architecture.
Strong foundation in object oriented programming principles, with the ability to design modular, extensible, and maintainable systems at scale; proficiency in Python preferred.
Proven experience building and operating large scale data platforms and data driven applications, with deep expertise in distributed data compute frameworks and large scale batch and streaming processing systems.
Deep expertise designing, implementing, and evolving REST and GraphQL APIs at scale, including schema design, versioning strategy, performance optimization, authorization patterns, backward compatibility, and developer experience for both internal and external consumers.
Hands-on experience with distributed data processing and streaming architectures, including Spark or similar compute engines, event driven systems such as Kafka, and speed layer query engines that support low latency, high volume data access patterns.
Demonstrated ability to architect and deliver end to end, production grade systems that orchestrate and automate complex, cross domain business workflows with strong reliability, observability, and long term maintainability.
Practical experience with LLM integration, RAG architectures, MCP, agent orchestration, or similar intelligent system patterns.
Experience operating in cloud native environments with modern CI/CD practices.
Demonstrated ability to influence architectural direction across multiple domains.
Strong ability to navigate organizational boundaries and operate autonomously at a strategic level.
Bachelor’s degree in Computer Science, Computer Engineering, or related field required.

Nice To Haves

Master’s degree preferred.

Responsibilities

Serve as the technical authority for one or more domains, owning architectural direction and long term system health across multiple business functions.
Translate strategic business priorities into scalable backend, data, and AI architectures that support sustained growth and enterprise adoption.
Define and evolve the architecture of large scale data platforms and backend services, including distributed compute, streaming systems, low latency query layers, and API surfaces.
Establish durable data modeling standards across operational and analytical domains to ensure consistency, scalability, and long term maintainability.
Lead the design of production grade AI systems, including LLM integration, Retrieval Augmented Generation pipelines, and agent based orchestration patterns.
Define enterprise standards for AI service abstraction, governance, evaluation, observability, performance, and cost management.
Deliver cross cutting architectural patterns and reference implementations that shape engineering practices beyond a single team.
Anticipate structural and scaling risks, and guide systems toward the desired future state through deliberate, iterative modernization.
Partner with product, analytics, and platform leaders to convert high value opportunities into robust, production systems.
Act as a hands on technical leader, contributing high leverage code, mentoring senior engineers, and raising execution and AI native engineering standards across the organization.