Senior Software Engineer (SRE)

UiPath•Denver, CO

20h

About The Position

At UiPath's Site Reliability team, we build the platforms and systems the entire company depends on to deliver on our compliance and SLA promises to customers. These span services and tools that enforce cloud access policies, cost governance, observability, operational excellence, and reliability across UiPath. We are scaling each of these pillars, and building the next generation of capabilities on each, powered by AI. This is a software engineering role. You will not be the person who identifies a reliability gap and files a ticket for another team to fix. You are the engineer who identifies the gaps across teams, designs the system that closes it, builds it, ships it, and drives its adoption — often by doing the integration work yourself rather than asking other teams to come to you. You build platforms that other engineers depend on in their critical path, and you hold yourself accountable to outcomes, not outputs. You treat every system you ship as a product: you put it in front of users early, seek feedback aggressively, and iterate until it delivers real results. If adoption is slow, you don’t blame the docs — you sit with the team, understand the friction, and remove it.

Requirements

Proven track record (6+ years) of architecting and engineering world-class, large-scale, distributed commercial applications and services, and ensuring customer success.
Experience building large-scale, complex internal platforms adopted by multiple teams in their critical path at a large company — systems that have stood the test of time, not prototypes that were handed off or abandoned.
Demonstrated ability to drive adoption of your systems by doing the hard work yourself: writing integrations, removing friction for other teams, and measuring success by outcomes delivered — not features shipped.
Experience building and maintaining complex AI-powered applications in production.
Proficiency in one or more object-oriented languages (such as C#, C++, Go, or Python), backed by solid computer science fundamentals.
Deep understanding of data structures, algorithms, multithreading, synchronization, asynchronous patterns, and cloud programming.
Experience with service-oriented and microservice-based architectures, HTTP applications, and web services development.
Familiarity with modern engineering practices including agile development, CI/CD, and DevOps.
Ability to work with globally distributed teams.
Experience with any of the cloud providers (Azure, AWS, GCP) and managed services (AKS, GKE, etc.) is a must.
Experience with database backends (e.g., Azure SQL, CosmosDB, Azure Data Lake, Power BI, MongoDB, MySQL, DynamoDB, etc.)

Nice To Haves

Experience working with or managing production Kubernetes infrastructure is a plus.

Responsibilities

Design, engineer, and build SRE platform systems and capabilities with cutting-edge AI, treating them as products that other engineering teams depend on in their critical path.
Participate in livesite monitoring rotations, handle escalations, and drive effective mitigations — aggressively reducing customer impact through broad, detailed, and effective postmortems.
Drive availability, scalability, and performance improvements based on livesite learnings.
Generate (or codify existing) best practices and ensure they are followed widely across UiPath — not by publishing guidance, but by embedding them into the systems you build.
Ensure technical deliverables meet or exceed expectations on reliability, scalability, quality, and performance.
Identify and drive architectural changes that significantly move the needle on these dimensions.
Onboard other teams onto your platforms by driving outcomes yourself — writing the integrations, pairing with their engineers, removing friction — rather than handing off documentation and waiting.
Ship early, seek feedback relentlessly, and iterate fast.
Treat every user complaint as a design input, not a support ticket.
Drive task planning, estimation, scheduling, and staffing.
Participate in and influence process improvements and best practices across the engineering organization.