Solutions Engineer in the DevOps Domain Consulting team, acting as a technical advisor and subject matter expert for Idira secrets management solutions.
Compensation
$173,000.00 - $237,500.00/yr
Responsibilities
Build and deliver product demonstrations and sales presentations to create excitement around Idira technology.
Conduct POC evaluations of Idira products with prospective customers.
Act as the technical expert and trusted advisor for machine identity security solutions during the sales cycle.
Partner with Account Executives to articulate the value of Idira’s solutions to technical and business stakeholders.
Conduct technical discovery sessions to understand customer environments, challenges, and security goals.
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus.
Responsibilities
Design, implement, and test enhancements to Control APIs and services, including rule evaluation, policy enforcement, advanced optimizations, and real-time usage insights, using Go on Kubernetes / GCP.
Build scalable systems for telemetry shaping and cost control, such as ingest policies, aggregation, sampling policies, utility scores & recommendations, and usage-based controls.
Partner closely with Product and Design to deliver customer-facing experiences that make it easy to understand telemetry cost drivers and take safe, effective action.
Own the operational quality of what you ship: instrumentation, alerting, debugging, incident response, and performance tuning for production workloads.
Collaborate across product, design, platform, infrastructure, and developer experience teams to integrate Control decisions into the broader ingestion, query, and storage ecosystem.
Lead the technical roadmap and ship features that redefine how teams collaborate during mission‑critical moments for Chronosphere’s observability platform.
Compensation
$147,000.00 - $237,500.00/yr
Responsibilities
Directly impact how customers leverage observability for their infrastructure and services architecture
Leverage AI infrastructure like LLMs, ML to build innovative capabilities for our customers
Design experiences and systems for contextualizing large amounts of telemetry data
Help shape the architecture of a rapidly scaling platform
Collaborate with deeply technical teammates and customers
Lead and architect backend alerting solutions for a cloud-native observability platform.
Compensation
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus.
Responsibilities
Design, implement, and ship enhancements and new features to core product capabilities using Go, deployed on Kubernetes across cloud platforms such as AWS and GCP
Design, implement, and deliver complex product features that address key customer pain points, collaborating closely with cross-functional teams—including product management, design, and engineering—to ensure alignment and impact throughout the development lifecycle.
Work closely with talented engineers in a fast-paced environment that fosters accelerated learning, continuous growth, and career development
Think beyond implementation—challenge assumptions, refine designs based on user feedback, and take ownership of delivering polished, effective user experiences.
Lead development of user experiences that surface critical insights at a glance, streamline troubleshooting, and reduce cognitive load during high-pressure situations.
As a Machine Learning Engineer on our Internet Security Research Team, you will be a key innovator transforming ideas into products for our next-generation security platform.
Compensation
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.
Responsibilities
Perform in-depth data analysis to deeply understand security data and the threat domain.
Design, train, and evaluate machine learning algorithms to significantly improve the analytical performance of threat detection models.
Build and productionize machine learning models and develop the distributed systems that utilize them to analyze and categorize enormous volumes of URLs.
Design and build robust, scalable machine learning systems, carefully balancing cost with model performance.
Establish automated training pipelines and develop data analytics tools to incrementally enhance model performance on a growing dataset.
You will join a Research and Development (R&D) team that will give you the opportunity to make a global impact, protecting our way of life in the digital age by preventing successful cyber attacks.
Compensation
$90,000.00 - $147,500.00/yr
Responsibilities
Collaborate with cross-functional teams to design, develop, and deploy software solutions with agility and rapid iteration.
Use and experiment with AI-assisted development tools (e.g., Cursor, Claude Code) to boost productivity and improve code quality.
Help define and evolve new engineering practices that leverage AI for code generation, testing, documentation, and refactoring.
Write clean, maintainable, and well-documented code, and actively participate in peer reviews and team design discussions.
Contribute to the automation of development, deployment, and monitoring processes as part of a DevOps culture.
Requirements
Bachelor's degree in Computer Science, Software Engineering, Machine Learning, or a similar technical field