Staff Software Engineer

This role is for a staff engineer who independently leads the design, development, and delivery of complex, high-impact AI-native and cloud-native systems. The IC4 engineer takes ownership of critical components or features, sets technical direction within their domain, and serves as a technical resource to peers and junior engineers. They combine deep software engineering fundamentals with hands-on expertise in AI/ML integration, cloud architecture, and production systems. This role requires the ability to balance technical depth with organizational impact, working across teams to solve ambiguous problems and drive platform improvements. Responsibility Area: Technical Leadership & Architecture •    Lead the design and architecture of complex, production-critical AI-native systems, including LLM integrations, agentic workflows, retrieval pipelines, and inference services •    Own end-to-end delivery of medium-to-large features or systems, including specification, design, implementation, testing, deployment, and production monitoring •    Make informed architectural and technical trade-off decisions between latency, cost, scalability, reliability, and model quality •    Establish evaluation frameworks, testing strategies, and production monitoring for AI-driven features; drive adoption of eval-driven development practices •    Design and optimize high-performance data pipelines, embedding systems, and vector stores handling millions of rows and complex retrieval scenarios •    Champion security best practices, including prompt-injection defense, data privacy, PII handling, responsible AI guardrails, and compliance with regulatory requirements •    Participate in architectural reviews across teams and contribute to platform-level technical decisions •    Stay current with emerging AI/ML frameworks, services, and techniques; evaluate and recommend adoption where applicable Responsibility Area: Mentorship & Technical Influence •    Mentor junior and mid-level engineers (IC2/IC3) through pair programming, design reviews, architecture discussions, and hands-on coaching •    Conduct thorough code reviews, including evaluation of prompts, agent logic, retrieval strategies, and AI/model behavior validation •    Identify technical debt and improvement opportunities; advocate for and lead initiatives to address them •    Share knowledge through documentation, brown-bag sessions, and architectural guidance •    Contribute to hiring and interview processes; provide technical assessment and feedback on engineering candidates •    Model best practices in software craftsmanship, testing discipline, and debugging methodology •    Support onboarding of new team members and ensure knowledge transfer across projects Responsibility Area: Cross-Functional Collaboration & Communication •    Work closely with product management, domain specialists, and other engineering teams to define requirements and technical specifications •    Translate complex technical concepts and AI trade-offs for non-technical stakeholders (product, leadership, customers) •    Lead root cause analysis for customer-reported issues, including those involving model behavior, hallucinations, retrieval quality, and distributed system complexity •    Participate in design reviews, technical planning sessions, and retrospectives; contribute perspectives on technical feasibility and risk •    Communicate clearly about design decisions, implementation challenges, AI limitations, and production incidents •    Build and maintain relationships with adjacent teams and external partners where applicable •    Proactively identify opportunities to improve development processes, tooling, and team efficiency Responsibility Area: Software Development Excellence •