R&D Principal Software Engineer

You’ll fit right in if you're someone who adopts a first-principles approach to problem-solving, love deep-diving into distributed systems to optimize scale and performance, and enjoy the challenge of making data flow seamlessly at a massive scale.

This on-site position is based in Palo Alto, California. You will join a global, cross-border team of talented engineers operating across India, Germany, and the USA.

Key Responsibilities

As a Principal Engineer, you will be architecting and building high-performance, cloud-scale analytics and security solutions. You will play a critical role in envisioning and delivering highly resilient, microservices-based solutions that process massive streams of telemetry for application performance, security, and intelligence.

• Architectural Leadership: Lead the design and implementation of distributed microservices for low-latency data processing and high availability.

• Scale & Performance: Build and optimize data pipelines capable of handling millions of records, ensuring the platform scales elastically in hybrid environments.

• Tech Stack Orchestration: Leverage a sophisticated stack to build durable, stateful workflows to manage complex backend processes.

• Data Strategy: Design schemas and optimize queries across a polyglot persistence layer (OpenSearch, PostgreSQL, Redis, and Neo4j) to provide time sensistive insights to customers.

• Mentorship: Act as a key technical leader by conducting deep-dive code reviews, driving engineering best practices, and mentoring junior engineers.

Required Skills & Experience

Professional Experience

• Education: BS/MS in Engineering Computer Science or a related technical field.

• Minimum of 12+ years of experience in software development with a focus on backend systems.

• Proven experience leading the end-to-end lifecycle of a product, from initial design to production deployment and maintenance.

Programming Proficiency

• Expert Level (GoLang & Python): Deep mastery of Go (concurrency, profiling, and performance tuning) and Python (data manipulation and backend services).

• Moderate Level (C++): Ability to maintain and optimize performance-critical components or interface with lower-level system libraries.

Cloud-Native Architecture & API Design

• Microservices at Scale: Proven experience designing and delivering production-grade microservices for high-throughput, cloud-scale environments.

• Communication Protocols: Proficiency in gRPC, Google Protocol Buffers (Protobuf), and RESTful API design, with a deep understanding of the HTTP/S stack.

• Data Persistence & Search: Hands-on experience with one or more of the following: OpenSearch/Elasticsearch, PostgreSQL, Redis, or Neo4j (or their equivalents).

Desired Skills & Qualifications

• Networking Domain Expertise: Strong understanding of L4–L7 networking, TCP/IP, HTTP/S protocols, and load-balancing principles.

• Advanced Data Engineering: Background in building data pipelines specifically for security and intelligence platforms (e.g., threat detection, anomaly detection, or predictive analytics).

• Analytics Background: Familiarity with time-series data, stream processing, and large-scale data visualization backend logic.

• Data Science Tools: Experience with data modeling and statistical analysis using Python libraries such as Pandas, NumPy, and Scikit-Learn.

• Orchestration: Working knowledge of Kubernetes and experience with Temporal (or similar workflow engines like Cadence) for managing distributed transactions.