Job Details

Responsibilities

• Build and Enhance AIOps Systems Design and implement components of the AIOps platform to deliver monitoring and analytical applications that leverage ML/AI for anomaly detection, event correlation, and incident automation.
• Operational Problem-Solving Collaborate with SREs and DevOps teams to address system reliability issues through intelligent monitoring and automated remediation.
• Data-Driven Engineering Work with large datasets (logs, metrics, traces) to develop pipelines and ensure data quality for observability and predictive analytics.
• Automation Development Contribute to workflows that reduce manual operational tasks, building self-healing and auto-scaling solutions.
• Cross-Team Collaboration Participate in design discussions with architects, senior engineers, and product teams to align solutions with organizational needs.
• Continuous Learning and Improvement Evaluate new frameworks and integrate incremental improvements into the AIOps ecosystem.
• Ownership Take responsibility for features from design through deployment and support, ensuring quality and reliability.

Qualifications

• Bachelor's or Master's degree in Computer Science, IT, Data Science, or a related field.
• 8+ years of software development experience in Python, Golang, or similar languages.
• Proven experience building cloud-native applications and services.
• Hands‑on experience with at least one major cloud platform (AWS, GCP, or Azure).
• Strong experience with containers, Kubernetes, and CI/CD tooling and practices.
• Solid development experience building and integrating RESTful APIs and working with platform tools such as Postgres, MongoDB, Kafka, Redis, Prometheus.
• Experience with Linux systems: administration, troubleshooting, shell scripting, and core OS concepts.
• Adaptable to dynamic environments and a proactive, fast learner.
• Strong analytical and problem‑solving skills.

• Deep familiarity with observability stacks (Prometheus, Grafana, ELK, Open Telemetry).
• Advanced knowledge of Kubernetes internals, container orchestration patterns, and service mesh technologies.
• Experience with AI/ML data engineering workloads and pipelines.
• Networking expertise: TCP/IP, DHCP, DNS, IPSec, network namespaces, routing, and switching.

Compensation and Benefits

Salary range for this position depends on location, and on the candidate's knowledge, qualifications, skills, education, training, and experience.

Pay ranges by region:

• Bay Area (including Marin, San Francisco, San Mateo, Santa Clara): 191,200‑250,950 USD
• California non‑Bay Area, Washington, New York, New Jersey, District of Columbia: 174,800‑229,425 USD
• Colorado, Hawaii, Maryland, Illinois, Minnesota: 162,000‑212,625 USD

Short‑term variable compensation is offered as an annual bonus based on performance.

Health benefits include three medical plan options and a dental plan option, with company credits equal to the cost paid toward premiums.

401(k) Plan offers an automatic 3% company contribution and matching contributions up to 5% of eligible pay.

Paid time off includes 15 days of vacation, 3 personal days, 11 holidays, 8 volunteer hours, and 80 sick hours annually, prorated by start date.

EEO Statement

Ericsson is proud to be an Equal Opportunity employer. Learn more.

Disclaimer

DISCLAIMER: The above statements are intended to describe the general nature and level of work being performed by employees in this position. They are not an exhaustive list of all responsibilities, duties and skills required for this position, and you may be required to perform additional job tasks as assigned.