Principal Software Engineer - Agentic AI Development - Distributed Systems - $110K - $120K

Principal Software Engineer Gen AI

Role Overview:

As a Principal Software Engineer within Product Engineering, you will provide cross-team technical leadership, shaping architecture, defining engineering standards, and driving long-term platform strategy. You will partner closely with engineering leadership, product teams, and cross-functional stakeholders to translate business goals into scalable, resilient, and future-ready systems.

This role requires a balance of strategic influence and hands-on execution. You will guide complex architectural decisions, mentor senior engineers, establish engineering best practices, and ensure technical consistency across distributed, multi-region teams.

Key Responsibilities:

• Own and evolve the architecture of large-scale, distributed, enterprise-grade SaaS platforms.
• Define and drive technical vision, architectural standards, and design principles across teams.
• Lead the design and delivery of complex, high-impact systems and services.
• Align technical strategy with business objectives in collaboration with product and engineering leadership.
• Review and approve critical design proposals, providing guidance on scalability, reliability, performance, and trade-offs.
• Contribute hands-on to core components, prototypes, and high-risk technical areas.
• Establish and enforce standards for code quality, testing, security, and operational excellence.
• Mentor senior and staff engineers, elevating the technical bar across the organization.
• Champion availability, resilience, scalability, and predictable delivery practices.
• Influence Agile execution, release planning, and cross-team dependencies across multi-region environments.

Required Qualifications:

• 8+ Years of professional software engineering experience with demonstrated technical leadership.
• Expert-level proficiency in Java, Python, Go, or Rust.
• Proven experience designing and operating large-scale distributed systems and microservices architectures.
• Strong expertise in API design and communication protocols including REST, WebSockets, gRPC, and MCP.
• Hands-on experience with relational and document databases such as PostgreSQL and MongoDB, including data modeling and performance optimization.
• Deep understanding of data structures, algorithms, concurrency, and system design principles.
• Experience building and integrating LLM-powered systems, including RAG pipelines and large-scale vector search.
• Hands-on experience with agentic frameworks (e.g., LangChain, LangGraph, crewAI) and multi-agent system design.
• Experience leading and influencing distributed teams across regions and time zones.
• Strong analytical and decision-making skills in ambiguous and complex environments.

Preferred Qualifications:

• Experience with distributed data and streaming systems such as Kafka, Redis, and ClickHouse.
• Strong background in Linux production environments and cloud-native deployments.
• Knowledge across database paradigms including SQL, NoSQL, time-series, graph, and vector databases.
• Experience designing AI/ML platforms, including MLOps and LLMOps for production-scale systems.
• Experience defining and managing SLOs, SLAs, and service reliability frameworks for AI services.
• Hands-on experience with LLM observability, including tracing, evaluation, monitoring, and guardrails.
• Familiarity with LLM fine-tuning approaches such as LoRA, QLoRA, instruction tuning, or full-parameter tuning.
• Proven ability to evaluate emerging technologies and drive adoption based on business impact.