Staff Software Engineer, Data & Scalability Platform

About this role

Staff Software Engineer, Data & Scalability Platform

Product and Engineering

2026790

Hybrid

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Job Description

The application window is expected to close on: 10/31/2026

This is a Hybrid position requiring Tuesdays and Thursdays on-site. In CA, the on-site requirement is Tuesdays in San Francisco and Thursdays in San Jose, CA; in NYC, Tuesdays and Thursdays are on-site in our NYC office.

The Splunk Agent Resilience team is defining the future of AI resilience. Our team provides scalable, cost-effective evaluation and guardrails that ensure AI agents behave as intended, improving reliability and reducing risks. This unified approach empowers our customers to confidently deploy and run AI-powered applications with enhanced observability and control.

As a Staff Software Engineer on the Data & Scalability Platform team, you will provide technical leadership for the architecture, scalability, and cost of the entire data plane: the stores that hold the data, the streaming and compute components that move and transform it, and tooling proving how all of it behaves under load. You will define the multi-quarter, technical direction for that data plane, establish the standards other teams build against, own the initiatives that keep it fast and correct as it grows by orders of magnitude, and influence the technical direction of the platform with engineering team leadership and product teams.

Your Impact

Define and drive the multi-quarter technical roadmap for the data platform — storage, streaming, compute, and the tooling that measures them.

• Lead the architecture and evolution of the data plane, including storage engine selection, sharding and tenancy models, and control/data plane boundaries.
• Establish platform-wide standards for schema design, migration safety, retention of data, and lead the review process that enforces them.
• Lead the capacity and performance model, and define the SLOs that set the definition of what correct and fast mean.
• Lead major scalability and performance initiatives spanning data stores, streaming pipelines, and distributed worker fleets.
• Drive cost efficiency, the cost per unit of telemetry, cost attribution, and quota and rate-limit design.
• Set the direction for multi-tenant isolation so that no tenant can degrade another.
• Design and build the internal frameworks and performance tooling — load testing, profiling, and benchmarking — that other engineers rely on to support design and capacity decisions.
• Establish observability standards for the platform so signals are correct, complete, and affordable.
• Lead the most production investigations and drive systemic remediation rather than point fixes.
• Make and document technology-selection and build-versus-buy decisions, with explicit cost, risk, and migration analysis.
• Partner with engineering leadership to influence platform direction and investment, and represent the data platform to the product teams building on it.
• Mentor engineers and raise the engineering bar through design reviews, technical standards, and documentation.

Minimum Qualifications

• Bachelor's degree with 8+ years of related experience, or Master's degree with 6+ years, or PhD with 3+ years, in Computer Science, Software Engineering, or a related field — including at least 6 years building and/or operating data-intensive backend services and/or platforms.
• Technical leadership experience, including experience setting technical direction, driving multi-quarter initiatives, and/or influencing decisions beyond your immediate scope.
• Experience with designing, operating, and/or delivering highly scalable, reliable, production-grade data-intensive platforms. Experience designing large-scale distributed systems and solving problems of scalability, availability, performance, reliability, and/or fault tolerance.
• Backend software engineering experience with either Go, Java, Rust, C++, and/or Python. Experience with cloud-native technologies, containerized environments (Kubernetes), and public cloud platforms (AWS, GCP, or similar)

Preferred Qualifications

• Demonstrated performance engineering ability — profiling, benchmarking, and load testing real systems, and turning the measurements into capacity, design, and cost decisions.
• Experience operating and tuning both an OLTP database (e.g., PostgreSQL, MySQL) and an analytical, columnar, or time-series store (e.g., ClickHouse, Druid, BigQuery, Snowflake) at production grade at scale — schema design, indexing, query tuning, and migration safety.
• Deep production experience with streaming or queueing systems (e.g., Kafka, RabbitMQ, Pulsar, Kinesis) — partitioning, consumer-group semantics, delivery guarantees, and backlog and dead-letter handling.
• Experience scaling data-processing compute — queue consumers, async task workers, or streaming jobs — including concurrency tuning, batching, backpressure, and throughput behavior under sustained load.
• Deep experience running ClickHouse or a comparable columnar store at scale — sharding and replication topology, materialized views, merge and mutation behavior, retention and TTL mechanics.
• Experience with a capacity model or a FinOps practice at platform scope: cost per.unit of telemetry, cardinality governance, and quota or rate-limit design.
• Experience designing multi-tenant isolation and noisy-neighbor mitigation in shared data systems.
• Experience leading a significant data migration or storage-engine transition in production without customer-visible impact.
• Experience defining SLOs for data services and driving an organization to meet them.
• Experience with backup and restore, tested disaster-recovery drills against stated RPO/RTO, and data retention or deletion compliance (e.g., GDPR/DSR hard delete).
• Experience building observability instrumentation and pipelines (OpenTelemetry, collectors, metrics/tracing backends) rather than only consuming dashboards.
• Experience building or operating performance tooling as a product for other engineers — the load-test harnesses, continuous profiling and flame-graph workflows (e.g., Pyroscope), or benchmarking suites.
• Experience with distributed task frameworks and worker orchestration (e.g., Celery, Temporal, Flink, custom consumer fleets) at production scale.
• Familiarity with streaming databases, stream processing frameworks, or distributed query engines (e.g., RisingWave, Flink, Spark Streaming, Trino/Presto) and with model-serving infrastructure.
• Experience supporting stateful systems in both cloud/SaaS and air-gapped or on-prem deployments.
• Experience mentoring senior engineers and raising engineering standards across multiple teams. Strong communication with the ability to turn performance, capacity, and cost findings into clear recommendations for engineering leadership, and product partners.

Why Cisco?

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

Message to applicants applying to work in the U.S. and/or Canada:

The starting salary range posted for this position is $186,900.00 to $267,700.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation\*, equity, or benefits.

Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.

U.S. employees are offered benefits, subject to Cisco’s plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.

U.S. employees are eligible for paid time away as described below, subject to Cisco’s policies:

• 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees
• 1 paid day off for employee’s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco
• Non-exempt employees\\ receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees
• Exempt employees participate in Cisco’s flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)
• 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next
• Additional paid time away may be requested to deal with critical or emergency issues for family members
• Optional 10 paid days per full calendar year to volunteer

For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco’s policies.