Staff Software Engineer

Confluent3 days ago

Location

Mountain View, California

Workplace

Remote

Type

Full Time

Salary

USD 235,700 – 277,000

Level

Staff

Role

Staff Software Engineer

Posted

Jul 22, 2026

Full TimeRemoteStaff

The role

Summary

Staff Software Engineer at Confluent will design and build backend services (Go, Java, Python) for real-time AI inference on streaming data within Confluent Cloud. This role requires 10+ years of distributed systems experience and demands end-to-end ownership of complex, cross-team technical initiatives spanning model lifecycle management, inference routing, and agent execution on production infrastructure.

What you'll do

Design and Build AI Inference Backend Services: Design and develop scalable backend services primarily in Go, Java, and Python that execute AI model inference and agent execution on real-time streaming data within the Confluent Cloud platform, ensuring low-latency performance and high throughput.

Own End-to-End Feature Delivery: Take full ownership of significant product features from conception through production, including drafting comprehensive technical designs, aligning stakeholders across teams, driving design decisions to completion, and managing the complete delivery lifecycle.

Make Cross-System Technical Decisions: Lead technical architecture decisions across multiple interconnected systems including model lifecycle management, inference request routing, agent orchestration, and inference serving layers, ensuring coherent system design and operational excellence.

Ensure Production Quality and Reliability: Maintain high standards for code quality, comprehensive test coverage, clear documentation, operational observability, and safe deployment practices for production inference infrastructure serving live traffic, with emphasis on reliability and incident prevention.

Mentor and Lead Technical Excellence: Elevate team capability through thorough code reviews, constructive design feedback, and personal accountability for complex cross-cutting technical work, building trust and establishing yourself as a go-to technical leader for ambiguous problems.

Participate in On-Call Rotation and Operations: Maintain operational responsibility for services owned by the team through on-call participation, incident response, and proactive process improvements to ensure sustainable team operations and continuous service health.

What we look for

Technical

Distributed Systems ArchitectureDeep expertise designing, building, and operating distributed systems and cloud-native backend infrastructure in production environments at scale, including experience with system design tradeoffs, failure modes, and resilience patterns.

Kubernetes and Container OrchestrationStrong working knowledge of Kubernetes architecture, deployment patterns, and operational best practices, combined with deep understanding of containerization technologies and container networking fundamentals.

Distributed Systems PatternsProficiency with distributed systems design patterns including control loops, API server architecture, high-scale control plane design, eventual consistency models, and consensus algorithms in production systems.

Multi-Language Backend DevelopmentProficiency in at least one of Go, Java, or Python with demonstrated ability to work effectively across all three languages, understanding language-specific performance characteristics and ecosystem tooling.

Backend Infrastructure and DevOpsExpertise in building and operating production backend infrastructure, including logging, monitoring, alerting, tracing, infrastructure-as-code, CI/CD pipeline design, and deployment automation.

Education

Bachelor's Degree in Computer Science or Related FieldBachelor's degree in Computer Science, Software Engineering, or related technical discipline, or equivalent professional experience demonstrating deep computer science fundamentals.

Experience

Senior Distributed Systems Engineering10+ years of professional software engineering experience with at least 5-7 years focused on designing, implementing, and operating large-scale distributed systems in production environments.

Cross-Team Technical LeadershipDemonstrated track record of leading ambiguous, cross-functional technical initiatives that span multiple teams and systems, translating unclear requirements into actionable technical designs that gain stakeholder alignment.

Production Infrastructure OperationsSubstantial experience owning production systems end-to-end, including operational responsibility through on-call rotations, incident response, postmortem analysis, and driving operational improvements.

System Design and ArchitectureExperience making high-impact architectural decisions for complex backend systems, considering scalability, reliability, cost, and maintainability across multiple services and deployment environments.

Skills

Required skills

Go ProgrammingProficiency in Go for building high-performance, concurrent systems with strong understanding of goroutines, channels, and Go's concurrency model.

Java DevelopmentStrong Java expertise including modern frameworks, JVM performance tuning, garbage collection, memory management, and building scalable backend services.

Python Backend DevelopmentSolid Python skills for backend service development, including async programming patterns, performance optimization, and integration with distributed systems.

KubernetesDeep knowledge of Kubernetes architecture, API objects, scheduling, resource management, networking, storage, and operational patterns for production deployments.

Distributed Systems FundamentalsCore knowledge of CAP theorem, consistency models, fault tolerance, replication, data synchronization, and consensus mechanisms in distributed systems.

API Design and RESTful ServicesExpertise designing clean, maintainable APIs for backend services, including request/response serialization, error handling, versioning strategies, and SDK development.

System Design and ArchitectureAbility to design large-scale systems considering scalability, reliability, latency, throughput, and cost tradeoffs, and to articulate design decisions clearly to technical and non-technical stakeholders.

Technical Communication and DocumentationExcellent written and verbal communication skills including ability to write clear design documents, architecture decision records (ADRs), and technical specifications that align cross-functional teams.

Nice to have

Model Serving InfrastructureExperience building or operating platforms for serving machine learning models at scale, including batching strategies, inference optimization, and model lifecycle management.

LLM and AI Agent InfrastructureExposure to large language model serving platforms, prompt management systems, or agent orchestration frameworks, understanding inference patterns and operational challenges.

Streaming Data SystemsExperience with streaming data platforms, event processing systems, or Kafka-based architectures, understanding real-time data pipelines and event-driven application patterns.

Apache KafkaFamiliarity with Apache Kafka architecture, broker design, consumer group management, and distributed topic partitioning for high-throughput event streaming.

gRPC and Protocol BuffersExperience implementing high-performance RPC systems using gRPC and Protocol Buffers for efficient service-to-service communication in distributed systems.

Cloud Platform ServicesExperience building on major cloud platforms (AWS, GCP, Azure) with understanding of managed services, auto-scaling, cost optimization, and cloud-native architecture patterns.

Observability and MonitoringStrong background in designing observable systems with distributed tracing, structured logging, metrics collection, and building dashboards for production system visibility.

Control Plane DesignExperience designing high-scale control planes that manage cluster state, coordinate distributed work, handle failures gracefully, and maintain consistency at scale.

Compensation & benefits

Salary

USD 235,700 – 277,000 (annual)

Stock options

Available

Benefits

Comprehensive Health Coverage

Medical, dental, and vision insurance options with competitive premiums, covering preventive care, specialist visits, and mental health services.

Retirement Planning

401(k) plan with employer match, helping you build long-term financial security with tax-advantaged savings options.

Paid Time Off

Generous vacation days, sick leave, and paid holidays enabling work-life balance and personal wellness.

Professional Development

Learning budget, conference attendance support, and access to online training platforms for continuous skill development and career growth.

Stock Options and Equity

Opportunity to participate in company equity through stock options or RSUs, aligning your success with Confluent's growth and providing wealth-building potential.

Flexible Work Arrangements

Remote-first culture supporting distributed teams across time zones with flexibility to work from home or office as needed.

Parental Leave

Generous parental leave policies supporting new parents during critical early months of childcare.

Wellness Programs

Fitness subsidies, mental health resources, wellness workshops, and employee assistance programs supporting holistic health.

Interview process

1
Initial Phone Screen — Recruiter conducts 30-minute conversation to assess background, career trajectory, motivation, and alignment with Staff-level expectations. Expect discussion of past distributed systems work and cross-team technical leadership examples.
2
Technical Architecture Discussion — Engineer-led 1-hour conversation focused on system design thinking. You'll discuss approaches to large-scale problems similar to those in the role, such as designing inference routing systems or model lifecycle management. Bring examples of systems you've designed.
3
Distributed Systems Deep Dive — Senior engineer conducts 1.5-hour technical discussion covering Kubernetes internals, distributed consensus, fault tolerance, and operational patterns. Prepare to discuss production incidents, failure scenarios, and how you've debugged complex distributed system problems.
4
Cross-Functional Collaboration Assessment — Meeting with engineers from different teams to evaluate communication skills, ability to make sound technical decisions across boundaries, and how you approach building alignment on complex initiatives.
5
Leadership and Vision Discussion — Conversation with engineering manager or senior tech lead about your technical vision, how you mentor other engineers, your approach to end-to-end ownership, and your perspective on building systems at scale.
6
Final Executive Round — Brief conversation with director or VP-level executive covering career aspirations, culture fit, and strategic thinking about building AI infrastructure on streaming platforms.