Title: Software Engineer III/Senior, AI Gateway Location: San Francisco United States Job Description: ngrok is an all-in-one cloud networking platform that secures, transforms, and routes traffic to services running anywhere. Instead of cobbling together nginx, NLBs, VPNs, model routers, and oodles of other tools, developers solve every networking problem with one gateway. Doesn't matter if they're sharing localhost or running AI workloads in production. We're trusted by more than 9 million developers at companies like GitHub, Okta, HashiCorp, and Twilio. What started as a way to put your local app on a public URL has grown into a universal gateway for API delivery, AI inference, device fleets, and site-to-site connectivity. It's the same ngrok that millions of developers have loved and leaned on every day for years, now with the power to run production traffic at scale. A few things you should know: - We are obsessed with our pets, Viper sunglasses and Bufo (yes, the toad) - We have a designated Chief Emoji Officer - they are vital to our success! - We like software that's serious and culture that's not About the AI Gateway Team Our AI Gateway team builds the systems that define how AI traffic is identified, controlled, and understood as it passes through ngrok. We own the AI-specific control plane at the gateway layer: policies, usage tracking, and enforcement that sit directly on live customer traffic. Our systems must behave correctly under real-world conditions-traffic spikes, unexpected model behavior, misconfigured policies, and customers asking, "Why was this blocked?" or "Where did my tokens go?" What You'll Actually Do - Build and evolve the AI Gateway: You'll work on the AI-aware gateway components that classify and handle AI traffic in real time. This code runs directly in the request path and must be fast, safe, and predictable. - Own AI traffic policy enforcement: You'll design and implement AI Gateway Traffic Policy Objects-rate limits, usage caps, and access rules specific to AI workloads. These policies exist to prevent runaway costs, misuse, and accidental exposure without breaking legitimate traffic. - Track AI usage and token consumption: You'll build and maintain systems that accurately measure AI usage-requests, tokens, and related metadata-so customers can understand how their AI systems behave and what they're consuming. - Make AI behavior observable and explainable: You'll expose clear, trustworthy signals around AI traffic: what was allowed or blocked, which policies applied, and how usage accumulated. When customers ask "what happened?", the gateway should already know. - Design abstractions that hide complexity: You'll work with product and design to build AI-specific gateway primitives that feel intentional and safe, without leaking provider quirks or infrastructure details into customer workflows. - Ship systems customers trust in production: You'll collaborate closely with Gateway, Customer Data, and Platform teams to ensure AI usage data, policy enforcement, and billing signals line up-so customers can turn these features on with confidence. You Might Be a Great Fit If… - You're comfortable in a statically typed, compiled language such as Go, Rust, C++, or Java (with bonus points for Go) - You've worked with AI/LLMs and can appreciate their unique brand of edge-cases - You care about developer experience and thoughtful abstractions - You enjoy defining system behavior, not just plumbing - You've thought about retries, limits, and costs before being asked - You like systems that move complexity from the user to the system Extra credit if you've worked on: - AI platforms or inference infrastructure - API gateways with product-level opinions - Usage limits, quotas, or billing-adjacent systems - Customer-facing observability tools Tech Stack ngrok runs entirely on AWS. Engineers develop by using remote development tools and/or ssh to connect to remote EC2 environments that run a full Kubernetes cluster of the ngrok stack, closely mirroring production. The codebase is primarily Go and TypeScript. We use Postgres for persistence, Kafka for streaming, Protobuf for service boundaries, and Kubernetes, Terraform, Helm, and Buildkite to operate and ship reliably. React is used for user interfaces, and GitHub supports our development workflows and remembers everything. Location This is a remote position for candidates outside of the Bay Area and a hybrid role for candidates within commuting distance to San Francisco. Our Bay Area employees commute to the office on Tuesdays and Wednesdays. Sponsorship All candidates must be US-based, and legally authorized to work in the United States. At this time, ngrok is unable to provide visa sponsorship for this position. Applicants must be authorized to work in the United States on a permanent, ongoing basis without the need for current or future sponsorship. Compensation Senior Software Engineer - Tier 1 (SF, LA, Seattle, NYC): $202,500 - $247,500 - Tier 2 (rest of US): $186,300 - $227,700 Software Engineer III - Tier 1 (SF, LA, Seattle, NYC): $180,000 - $220,000 - Tier 2 (rest of US): $165,600 - $202,400 Job level and actual compensation will be evaluated based on factors including, but not limited to, qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), internal equity with other team members, market data, and specific work location. We provide an attractive mix of salary and equity. #LI-Hybrid Full Time Employee Benefits - Health stuff that actually matters. Full premiums covered on base healthcare, dental, and vision for you. Half covered for your dependents. Mental health and well-being support included, because taking care of your brain is as important as taking care of your teeth. - Retirement matching that doesn't suck. 401(k) with 100% match up to 3% of your salary and 50% match up to another 2%. Future you will appreciate present you. - Actually flexible time off. We say "open, flexible vacation policy" and actually mean it. Take the time you need. Your manager will bug you if you're not taking enough. - Parental leave that's realistic. Up to 16 weeks if you give birth, up to 8 weeks for new parents (birth, adoption, fostering-however your family grows). - Money to keep growing. Annual professional development budget for books, courses, conferences, or whatever helps you level up. Plus an annual home office/desk stipend to make your workspace not terrible. - Work from wherever. Co-working space stipend if you want to get out of your house but aren't near our SF office. - Lunch on us. 2x+ per week for employees onsite at our San Francisco office. Free food tastes better. - Company offsites. Twice a year we get the whole team together. It's part strategy, part bonding, part excuse to hang out with Bufo (the toad). - Regular feedback and fair compensation. Bi-annual reviews to make sure you're getting real feedback and staying competitively compensated. No surprises, no waiting around for performance conversations.

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems. Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same. Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Analyse and identify the linkages and interactions between the component parts of an entire system. Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion. Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables. Develop skills outside your comfort zone, and encourage others to do the same. Effectively mentor others. Use the review of work as an opportunity to deepen the expertise of team members. Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate. Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements. The Opportunity As part of the People Tech & AI team you will lead teams delivering governed Generative AI solutions, designing testing strategies, evaluation frameworks, and governance controls to promote reliable, ethical, and scalable AI agents. As a Manager you will supervise teams, manage client accounts, and apply leading practices across AI platforms, data pipelines, and integrations, while upholding PwC's values and professional standards. This role offers the chance to drive innovation in AI technology while fostering a collaborative environment that empowers team members and enhances client relationships. Responsibilities - Foster a collaborative environment to enhance team performance - Uphold professional standards and PwC values in every deliverable - Drive innovation in AI technology to meet client needs - Supervise team members and support their professional development What You Must Have - Bachelor's Degree - At least 6 years of experience in AI/ML engineering, data engineering, or software engineering - In lieu of a Bachelor's Degree, demonstrating, in addition to the minimum years of experience required for the role, three years of specialized training and/or progressively responsible work experience in technology for each missing year of college What Sets You Apart - Master's Degree preferred - Proven experience leading AI solution teams - Demonstrating understanding of LLMs and agent architectures - Possessing experience with Microsoft Power Platform - Bringing prior consulting or professional services experience - Establishing testing and validation standards for AI agents - Managing and coaching teams for continuous development - Building trusted client relationships and translating requirements - Designing and overseeing automated testing frameworks for Microsoft Copilot Studio and Google AgentSpace, including unit, integration, end-to-end, and regression testing, as well as low-code workflows, connectors, plugins, and grounding data - Leading governance of end-to-end AI agent pipelines and data flows, verifying integration correctness and resiliency, data quality, lineage, transformation accuracy, and embedded automated quality gates across CI/CD pipelines The salary range for this position is: $73,500 - $212,280. For residents of Washington state the salary range for this position is: $73,500 - $244,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance As PwC is an equal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law. PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy. Learn more about how we work: https://pwc.to/how-we-work For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all. Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines #LI-Remote #LI-Hybrid #BI-Hybrid

• Join the Engineering team as a Forward Deployed AI Engineer • Act as a resident AI expert within Individual Departments/Business Units • Function as engineer, solutions architect, and internal consultant • Design and build AI-powered application features using LLM APIs • Create agent loops that can select tools, execute actions, and summarize results • Develop chat-based analytical experiences connecting user questions to backend tools • Improve prompt quality and manage context windows • Use advanced AI coding tools to accelerate development while maintaining code quality • Embed directly with internal departments to identify where AI can drive efficiency • Lead the end-to-end implementation of AI solutions within operational contexts • Provide hands-on troubleshooting and support for AI models running in production mode

• Lead the technical vision, design and operation of the company’s AI gateway and core AI enablement platform • Define and implement standards for approved AI providers, models, data sources, shared tools and usage patterns • Build and maintain controls for access, routing, policy enforcement, auditability and financial operations reporting across AI usage • Implement required identity, logging and related controls in alignment with broader IT and security standards • Partner through the AI Enablement Council to translate business needs into scalable platform capabilities and guardrails • Support onboarding, documentation and internal enablement for business teams using approved AI tooling • Evaluate gateway platforms and ecosystem capabilities to improve flexibility, governance and business value • Drive reliable platform operations, issue resolution and continuous improvement across the AI environment