Senior Staff Applications Development Engineer

Join our team as a Senior Staff Applications Development Engineer, where you will design, build, and operate AI-native industry applications. You will work across the full software development lifecycle, often embedded directly with customers, and drive engineering excellence while mentoring other engineers. Your responsibilities will include designing scalable enterprise applications, building autonomous workflows, and ensuring quality and reliability in production.

USD 190,900 - 334,100

Responsibilities

• You will also serve as a technical leader, partnering with product managers and stakeholders to translate complex business requirements into scalable technical solutions.
• Design, build, and deliver scalable, AI-native enterprise applications for industry-specific workflows, data models, and compliance requirements.
• Drive engineering excellence, mentor other engineers, and influence architecture and long-term platform direction across multiple teams.
• Work across the full software development lifecycle, and often embedded directly with customers as a forward deployed engineer, building against their data, integrations, and channels.

Requirements

• Deep domain experience in high-tech, and familiarity with adjacent regulated industries such as telecommunications, healthcare, financial services, or manufacturing, at a depth sufficient to challenge a requirement rather than only implement it
• Advanced knowledge with data structures, algorithms, object-oriented design, design patterns, and performance/scale considerations
• 10+ years of experience with Java or a similar OO language
• Specification precision and architectural judgment: the ability to define problems rigorously enough that another engineer or an AI agent implements them correctly, and to decide soundly when to solve a problem in code, in instructions, or by delegating to an agent
• Willingness to work directly with customers in a forward deployed capacity, with the judgment to know when a fast local solution is right and when to hold out for the durable one, and the credibility to communicate capability, limitation, and risk to non-engineers
• 10+ years of professional software engineering experience in the SaaS industry, building and operating products at production scale
• Bachelor's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience
• Advanced knowledge experience working with relational databases including development, troubleshooting and performance optimization
• A demonstrated track record of building, shipping, and operating production software, including hands-on delivery of AI-native application features that real users depend on rather than demos

Preferred qualifications

• Experience delivering conversational experiences in chat, voice, or both, including turn and context management, disambiguation and confirmation patterns, and automated-to-human handoff
• Prior forward deployed, solution engineering, or professional services experience delivering software inside a customer's environment
• Advanced command of data structures, algorithms, object-oriented design, design patterns, system design, APIs, and performance optimization
• Experience integrating AI into engineering workflows, decision-making, automation, or the software development process itself
• Strong grounding in modern application architecture across cloud, distributed systems, and service-oriented or platform technologies, with solid data modeling and storage fundamentals. Depth matters more than any specific language or framework
• Direct, hands-on experience authoring agentic instructions and prompts, designing AI-driven autonomous workflows, and building the evaluation and testing that verifies non-deterministic behavior
• Experience with multiple technology stacks: Cloud Dev, Platforms, Web Dev, Frameworks or service–oriented architecture
• Familiarity with modern UI frameworks (for example React, Angular, or Vue) and with evaluation, tracing, and prompt or instruction management tooling for LLM applications
• Prompt engineering and evaluation of non-deterministic systems: intent-driven prompt design plus measurable frameworks for response quality, agent behavior, tool-selection accuracy, and regression risk, iterating against evaluation results rather than impressions
• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry
• Passion for JavaScript and the Web as a platform, reusability, and componentization
• Working knowledge of safety, security, and data handling for AI-integrated applications: prompt injection, sensitive-data and secret leakage, over-broad tool access, and unsafe autonomous action, translated into concrete guardrails, least-privilege controls, and monitoring
• ServiceNow platform experience is recommended, including building configurable, extensible applications on the platform
• Experience with any of the modern UI frameworks like Angular, React or Vue
• AI-native application development: agent orchestration at the application layer, tool and function calling, context assembly, grounding against enterprise data, and handling latency, cost, and failure
• Capability to manage multiple projects with material technical risk across teams and processes; may serve as a functional lead or technical owner
• Demonstrated ability to lead technically complex projects across multiple teams as a technical owner or engineering leader, with strong communication, collaboration, and mentoring skills