• Build and Deploy AI Solutions: Design, build, test, and deploy AI-powered solutions aligned to client business requirements. • Support AI Enablement Engagements: Contribute across the full lifecycle of client AI programs, from discovery through deployment and adoption. • Facilitate AI Upskilling and Training: Help non-technical users understand, adopt and get value from new AI solutions. • Drive AI Tool Fluency and Teach Back: Explore and evaluate new AI tools and frameworks to stay current.

Role Description We're looking for a Full-Stack AI Engineer who builds production AI systems using Claude Code as a primary development tool. This role is for someone who combines strong full-stack engineering fundamentals with hands-on experience shipping AI-powered products, automations, and intelligent workflows into real environments. Claude Code is not optional here. You use it daily, you know how to get the most out of it, and it makes you meaningfully faster and better than engineers who do not. On top of that, you can design and build across the full stack, from backend services and APIs to frontend interfaces and AI integration layers, and you take ownership of systems end to end without needing close direction. If you build full-stack AI systems, ship automations that actually run in production, and use Claude Code as a core part of how you engineer, this role is built for you. Qualifications - 4+ years of professional software engineering experience with a strong full-stack background - Claude Code fluency: you use it daily in production and it is a core part of how you engineer - Demonstrated experience building and shipping full-stack AI systems in production including automations, AI agents, or LLM-integrated workflows - Strong system design fundamentals including APIs, databases, and distributed systems - Product-oriented mindset with strong ownership and the ability to execute without heavy oversight - Full availability during US business hours Requirements - Preferred but not strictly required: - Experience with TypeScript, Python, or similar backend technologies - Experience with modern frontend frameworks - Exposure to cloud infrastructure such as AWS or GCP - Experience with embeddings, vector databases, or retrieval systems Benefits - You will be paid in USD (bi-monthly: every 15th and 30th) - Paid Time Off in accordance with company policy - Observance of Holidays per company guidelines - 100% remote setup so you can work wherever you're most productive - High-ownership engineering role with direct impact on product and AI infrastructure - Opportunity to design and ship AI-powered systems from the ground up - Direct collaboration with product and engineering leadership How to Apply Please include: - Your updated resume - A short Loom video (1 to 2 minutes) walking through a full-stack AI system you built in production, how you used Claude Code throughout the development process, and what the system actually does Only candidates who submit a Loom video will be moved to the next step of the hiring process. Application Process Overview Our comprehensive selection process ensures we find the right fit for both you and our clients: - Initial Application - Submit your application and complete our prequalifying questions - Video Introduction - Record a video introduction to showcase your communication skills and work experience - Role-Specific Assessment - Complete a homework assignment tailored to the position (if applicable) - Recruitment Interview - Initial screening with our talent team - Executive Interview - Meet with senior leadership to discuss role alignment - Client Interview - Final interview with the client team you'd be supporting - Background & Reference Check - Professional reference verification - Job Offer - Successful candidates receive a formal offer to join the team Each stage is designed to evaluate your fit for the role while giving you insights into our company culture and expectations. We'll keep you informed throughout the process and provide feedback at each step.

Role Description You'll own the end-to-end technical relationship with enterprise customers, translating complex business challenges into high-impact AI solutions built on the Moveworks Platform. This is a customer-facing, field-based role — you'll be the primary technical point of contact throughout the full implementation lifecycle, from solution design through launch. You are equally comfortable whiteboarding with a customer's IT team in the morning and collaborating with internal engineering and product teams in the afternoon. This is not a back-office engineering role — you will be in front of customers regularly and are expected to travel up to 25% of the time. What You'll Own - Customer Technical Relationships: Serve as the primary technical owner across 5–8 enterprise customer engagements simultaneously, driving adoption and measurable outcomes across the full Moveworks implementation lifecycle. - Solution Design & Architecture: Partner with customers to architect and deliver high-impact AI solutions that solve real business challenges — leveraging the Moveworks Platform in innovative and meaningful ways. - Integration & Implementation: Design and build secure, performant integrations between the Moveworks Platform and customer enterprise systems including ServiceNow, Workday, Okta, Jira, and others. - Strategic Advisory: Serve as a trusted technical advisor, helping customers develop their Agentic AI roadmap and upskilling their teams to operate the platform independently over time. - Product Feedback Loop: Synthesize on-the-ground customer feedback and technical gaps, working directly with Moveworks Engineering and Product teams to influence platform evolution. - Reusability & Knowledge Sharing: Generalize successful customer solutions into reusable templates and share learnings broadly across the team. Qualifications - Required: - Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. - 5+ years of experience in a customer-facing technical role — Solutions Engineer, Customer Success Engineer, Solutions Architect, Implementation Consultant, or Consulting Engineer. - Demonstrated track record of driving successful technical adoption with mid-to-large enterprise customers. - Experience designing, building, and launching full-stack workflows and automations leveraging REST APIs, iPaaS tools (Workato, Azure Functions, AWS Lambdas, ServiceNow Flow Designer), or scripting languages (Python, JavaScript, Golang). - Willingness and ability to travel up to 25% of the time. - Ability to operate across multiple business functions and technical domains. - Preferred: - Familiarity with enterprise platforms such as ServiceNow, Jira Service Desk, Zendesk, Workday, or Okta. - Familiarity with Linux and Windows environments and command line. - Current on the latest AI tools, frameworks, and agentic design patterns — and thoughtful about how to apply them to build reliable, scalable solutions. Company Description It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started. Join us to put AI to work for people.

• Lead all technical implementation work for the AI Innovation Lab.**Design, set up, and maintain the technical infrastructure, including implementing a controlled AWS sandbox for safe exploration and development.**Establish guardrails and best practices for the development and testing of AI prototypes.**Execute initial pilots to validate AI concepts and use cases.**Build reusable patterns and templates within the AWS environment to ensure the lab builds repeatable capabilities.**Contribute to generating evidence-based recommendations for future productization of successful pilots.