Role Description Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based. What this opportunity involves: - Building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks. - Creating challenging tasks and evaluation criteria within realistic simulated environments: - Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history. - Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent. - Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient. - Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust. What this is NOT: - Not data labeling. - Not prompt engineering. - Not writing code from scratch - the agent writes most of the code; you guide and evaluate. Qualifications - 5+ years in software development. - Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis. - Experience writing tests (functional, integration). - English proficiency - B2+. Requirements - Deep understanding of where models fail and what scenarios reveal the difference between a good and a bad solution. - Ability to create tasks that genuinely challenge the best models. - Writing tests that accept all correct solutions and reject incorrect ones. Benefits - Compensation up to $50/hr equivalent, depending on level and pace. - Tasks are estimated at ~20 hours each; you set your own schedule. Effort Estimate Tasks for this project are estimated to take 20 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.

• Lead the implementation and continuous improvement of warehouse operations, processes, and performance across distribution sites • Optimize workflows, improve productivity, and ensure consistent execution of operational standards • Partner with Operations, Engineering, IT, and Analytics teams to analyze processes • Validate workflows and process changes to ensure safety • Analyze operational data to identify bottlenecks and inefficiencies • Design, analyze, and optimize warehouse layouts and workflows using industrial engineering principles • Develop and implement process improvements to reduce waste, cost, and cycle times using Lean or Six Sigma methodologies

Role Description Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based. What this opportunity involves: - Building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks. - Creating challenging tasks and evaluation criteria within realistic simulated environments: - Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history. - Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent. - Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient. - Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust. What this is NOT: - Not data labeling. - Not prompt engineering. - Not writing code from scratch - the agent writes most of the code; you guide and evaluate. Qualifications - 5+ years in software development. - Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis. - Experience writing tests (functional, integration). - English proficiency - B2+. Requirements - Deep understanding of where models fail and what scenarios reveal the difference between a good and a bad solution. - Ability to create tasks that genuinely challenge the best models. - Writing tests that accept all correct solutions and reject incorrect ones. Benefits - Compensation up to $40/hr equivalent, depending on level and pace. - Tasks are estimated at ~20 hours each; you set your own schedule. - Effort estimate: Tasks for this project are estimated to take 20 hours to complete, depending on complexity.

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. Job Description We are looking for a software engineer and technical lead with deep software design and architecture skills, excellent coding ability, and the technical judgment to build reliable production systems at enterprise scale. ServiceNow's core platform is built on a powerful and highly scaled Java service that supports some of the world's largest enterprise workflows. In this team, we are extending that platform with modern Python and Java microservices that complement the main platform architecture and enable new AI-native capabilities. These services are designed to run in Kubernetes-based environments while integrating deeply with the broader ServiceNow platform. We are focused on production-grade services that bring together enterprise data, AI model integrations, scalable APIs, evaluation workflows, and reliable deployment patterns. You will own the design, development, and operation of containerized backend services running in Kubernetes environments. You will apply strong distributed systems and production reliability judgment to build scalable, maintainable services, and you will lead technical design across ambiguous, high-impact problem spaces. Experience working on AI, GenAI, ML-powered, or data-intensive products will help you be especially successful in this role. Responsibilities - Designing, architecting, and implementing Java and Python microservices deployed on Kubernetes - Designing APIs, service boundaries, data models, and integration patterns for AI-enabled products - Building reliable distributed systems that handle concurrency, queueing, retries, fairness, backpressure, and failure recovery - Integrating frontier AI SDKs such as Anthropic, Google, and OpenAI into production software systems - Applying prompt engineering, structured outputs, model evaluation, and production observability to GenAI use cases - Partnering with research, product, security, and infrastructure teams to ship enterprise-grade services - Raising the engineering bar through architecture reviews, code reviews, mentoring, and technical direction Qualifications To be successful in this role, you have: - 8+ years of professional software engineering experience, with strong fundamentals in data structures, algorithms, distributed systems, APIs, and backend service design - Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving (including using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact) - Demonstrated experience as a technical lead, Staff Engineer, or equivalent senior individual contributor responsible for architecture, technical direction, code quality, and mentoring - Strong backend engineering skills in Java, Python, or equivalent with hands-on experience designing, building, and operating production services - Hands-on experience building or operating containerized applications deployed in Kubernetes, OpenShift, or similar orchestration environments - Experience designing scalable APIs, asynchronous processing systems, queues, event-driven services, or data-processing pipelines - Familiarity with cloud-native infrastructure, service observability, logging, monitoring, reliability engineering, and production troubleshooting - Ability to make pragmatic architecture decisions across performance, reliability, security, maintainability, and delivery speed - Ability to lead other engineers through code reviews, design reviews, and technical mentorship - Strong communication skills and the ability to partner across product, research, engineering, infrastructure, and security Nice to Have - Prior experience working on AI/ML products, collaborating with research teams, or translating advanced AI/ML capabilities into production software - Knowledge of NLP, search, and knowledge extraction - Experience with multi-modal systems such as document ingestion and processing, image processing, and voice - Working experience with frontier AI SDKs such as Anthropic, Google, or OpenAI - Familiarity with prompt engineering, structured outputs, tool calling, agentic design patterns, Model Context Protocol, or AI-assisted development workflows - Experience with observability tools such as Prometheus, Grafana, Instana, or equivalent monitoring/logging platforms - Knowledge of MLOps or applying machine learning models to production use cases - Experience with infrastructure backends such as PostgreSQL, Redis, Kafka, RabbitMQ, S3-compatible object storage, or equivalent technologies - Published work, patents, conference papers, or open-source contributions related to AI systems, knowledge systems, search, retrieval, or large-scale data processing. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. For positions in this location, we offer a base pay of $190,900 - $334,100, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.