Sequoia Senior Software Engineer
Posted Updated 8
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Summary
Senior Software Engineer at NetApp in Bangalore leading a team that builds scalable APIs and data platforms using Go, Python, PostgreSQL, Redis, and ClickHouse. The role blends hands-on technical leadership with CI/CD, observability, SRE practices, and AI-first engineering for automation and reliability.
Job Summary
We are looking for a Senior Software Engineer to lead a high-performing engineering team building scalable APIs and data platforms. You will own delivery and technical direction while driving AI-first engineering practices using automation and intelligent tooling to improve how we design, build, ship, and operate software. You will balance hands-on technical leadership with operational excellence, and a strong focus on quality and reliability.
Job Requirements
- Extensive experience designing, developing, and operating scalable applications using Go and Python, including REST and/or GraphQL APIs.
- Strong expertise in distributed systems, microservices, system design, scalability, reliability, and performance optimization.
- Deep knowledge of PostgreSQL, Redis, ClickHouse, or equivalent OLTP, caching, and analytics technologies.
- Experience with data modeling, query optimization, indexing, caching strategies, and analytics architectures.
- Hands-on experience with Data Lakehouse platforms, including ingestion, transformation, orchestration, governance, warehousing, and analytics.
- Strong background in data engineering and large-scale data processing systems.
- Experience with observability and monitoring tools such as ELK Stack and Grafana, including logging, metrics, tracing, dashboards, and alerting.
- Proven ability to build highly observable systems and perform root-cause analysis.
- Experience implementing CI/CD pipelines, automated testing, release automation, and deployment best practices.
- Strong understanding of software quality practices, including unit testing, integration testing, code reviews, static analysis, and technical debt management.
- Experience integrating security throughout the SDLC and driving secure development practices.
- Strong operational excellence mindset with production support, incident management, reliability engineering, capacity planning, and service health monitoring.
- Experience defining and managing SLOs, SLAs, operational runbooks, troubleshooting guides, and disaster recovery processes.
- Proven ability to lead architecture reviews, technical decision-making, and engineering best practices across platforms and services.
- Strong understanding of cloud-native development, containerization, orchestration, infrastructure automation, and Infrastructure as Code (IaC).
- Experience designing highly available, fault-tolerant, and cost-efficient systems.Strong collaboration skills, partnering with Product, Design, Program Management, and cross-functional teams to deliver business solutions.
- Demonstrated engineering leadership through mentoring, hiring, coaching, and fostering technical excellence.
- Experience adopting AI-first engineering practices to improve development, testing, code reviews, documentation, productivity, and operational efficiency.
- Knowledge of responsible AI adoption, governance, security, compliance, and quality controls.
- Experience leveraging AI for observability, incident triage, automation, root-cause analysis, and developer productivity.
- Exposure to Agentic AI, LLM orchestration, prompt engineering, tool-calling workflows, and AI-assisted automation preferred.
- Experience with RAG architectures, vector search, knowledge retrieval, and AI-powered applications is desirable.
- Background in streaming platforms, event-driven architectures, and large-scale analytics systems is a plus.
- Familiarity with enterprise security, compliance, auditability, and data governance in regulated environments.
Education
- IC - Typically requires a minimum of 8 years of related experience
- Bachelor’s degree or higher in Computer Science, Engineering, Information Technology, or a related technical discipline.
Skills
- Agentic AI
- AI
- Ai Enablement
- Analytics
- API
- Automation
- CI/CD
- ClickHouse
- Cloud
- Cloud Native
- Containerization
- Data Engineering
- Data Governance
- Data Modeling
- Distributed Systems
- ELK
- Event Driven Architecture
- Grafana
- GraphQL
- Infrastructure as Code
- Integration Testing
- Lakehouse
- LLM
- Microservices
- Observability
- PostgreSQL
- Program Management
- Prompt Engineering
- Python
- Redis
- Root Cause Analysis
- SDLC
- Test Automation
- Unit Testing
- Vector Search