Strong proficiency in Python and React (or equivalent)
Solid understanding of Linux, containers, and Kubernetes
High competency in applying GenAI tools in deployment environments
Entrepreneurial mindset with a customer-oriented approach
Responsibilities
Own product features including UI and APIs for detection
Build and support customer deployments in Linux and Kubernetes environments
Utilize GenAI tools for system work and ensure security
Design reliable and secure services with upgrade paths
Collaborate with customers and internal teams for effective integrations
Benefits
Work with cutting-edge technology in AI speech solutions
Join a passionate and innovative team
Collaborative and inclusive work environment
Contribute to impactful AI security technologies
Full Job Description
What you'll do
Own product features for detection: UI, APIs, workflows, and operational tooling.
Build and support customer deployments across Linux, Kubernetes, and on-prem/private cloud environments.
Use GenAI tools to accelerate systems work: incident/debug summaries, config generation, Helm/K8s troubleshooting, log analysis, release notes, and customer-facing docs-while keeping security and correctness high.
Design reliable, secure, observable services with clean upgrade/rollback paths.
Partner with enterprise customers and internal teams to deliver integrations that stick.
What we're looking for
Strong GenAI product fluency: you can apply GenAI tools to real-world infra + deployment work (logs, manifests, scripting, docs), and you're disciplined about verification in high-stakes environments.
Senior+ engineer with end-to-end ownership and systems thinking.
Strong in Python and React (or equivalent frontend).
Very comfortable with Linux, containers, Kubernetes, and enterprise constraints.
Entrepreneurial and customer-focused.
Bonus
Experience integrating model APIs and building internal tooling for ML product teams.
Previous startup experience in a high-ownership environment
Interview scorecard (what "great" looks like)
Shipping & ownership: takes features from vague idea 14 production with minimal hand-holding
Systems & deployment: strong Linux/K8s intuition; designs for operability
Execution cadence: keeps work moving, communicates clearly, unblocks without "managing"
