Principal Software Engineer

8+ years of experience designing, building, and operating high-scale, mission-critical cloud-based production systems.
Proven expertise in architectural patterns for distributed and federated microservices.
Mastery of at least one of these platforms: GoLang, Python, or Java.
Extensive experience in high-level service design with modular, composable, and extensible patterns.
Demonstrated success with data models, data stores, and data lake architectures (e.g., MongoDB, ClickHouse, Spark).
Experience developing and operating large-scale distributed systems with Kubernetes and Docker.
Track record implementing real-time and low-latency high-availability applications (using technologies like Kafka or gRPC).
Bachelor’s or Master’s degree in Engineering, Computer Science, or equivalent experience.
Strong leadership capabilities with the ability to influence, partner, and collaborate across engineering organizations.
Strategic thinking with the ability to balance technical leadership and business judgment when making technology decisions.

Design and drive the technical vision and architecture for scalable AI backend services.
Establish technical standards and drive the organization’s overall technical architecture, engineering practices, and methodologies.
Work on the organization’s most challenging problems, building high-quality, architecturally sound systems that align with business needs.
Create and implement reusable components, SDKs, and robust APIs that form the foundation of modular systems.
Develop and enhance tools, frameworks, and CI/CD pipelines that enable continuous delivery.
Mentor and coach engineers across the organization, inspiring technical excellence and growth.
Collaborate cross-functionally with product, design, and business teams to translate business requirements into elegant technical solutions.
Represent the organization in the technical community through contributions to open-source projects, technical publications, and industry forums.

Experience with AI infrastructure and technologies.
Knowledge of RAG (Retrieve, Augment, Generate) models and their practical applications in business systems.
Experience with agentic platforms and orchestrating multiple specialized agents for complex task management.
Expertise in speech technologies and natural language processing.
Experience with large language models (LLMs) and their integration into enterprise applications.
Strong knowledge of advanced database technologies including SQL, NoSQL, Time Series, and GraphDB systems.