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
•    Develop robust, maintainable, and well-tested AI-native software using Python, Java, and JavaScript as appropriate
•    Build comprehensive unit tests, integration tests, and AI evaluation harnesses (accuracy, regression, hallucination detection)
•    Troubleshoot complex issues in distributed systems, probabilistic models, and cloud infrastructure; isolate root causes efficiently
•    Implement secure coding practices and responsible AI guardrails throughout the development lifecycle
•    Manage deployment, monitoring, and iteration of features in production; respond to performance issues and model drift
•    Work with cloud services (AWS/GCP/Azure), managed AI services (Bedrock, Vertex AI, Azure OpenAI), Kubernetes, and CI/CD pipelines
•    Contribute to code and architecture standards; ensure adherence to established best practices

Responsibility Area: ServiceNow Platform Development
•    Design and develop custom applications, extensions, and integrations on the ServiceNow platform
•    Develop workflows, business rules, and automation using ServiceNow scripting (JavaScript, GlideScript, REST APIs)
•    Build data models, forms, and dashboards for ServiceNow applications; optimize database queries for performance
•    Integrate third-party AI/ML services and custom APIs with ServiceNow platform services
•    Contribute to and maintain ServiceNow plugin and app architecture; follow ServiceNow best practices and coding standards
•    Participate in ServiceNow upgrades and configuration management; ensure compatibility with platform updates
•    Mentor junior engineers on ServiceNow platform capabilities and development patterns

Responsibility Area: Customer Support & Product Excellence
•    Participate in customer issue triage and root cause analysis for production ServiceNow application issues
•    Work closely with customer success and support teams to understand and resolve complex technical issues
•    Provide technical guidance to customers on application usage, configuration, and troubleshooting
•    Identify patterns in customer issues and drive improvements to prevent recurrence
•    Contribute to customer documentation and internal knowledge bases
•    Support customer escalations; provide timely resolutions to critical issues affecting customer operations
•    Gather customer feedback and communicate product improvement opportunities back to product management