Method is a global design and engineering consultancy founded in 1999. We believe that innovation should be meaningful, beautiful and human. We craft practical, powerful digital experiences that improve lives and transform businesses. Our teams [based in New York, Charlotte, Atlanta, London, Bengaluru, Japan and remote] work with a wide range of organizations in many industries, including Healthcare, Financial Services, Retail, Automotive, Aviation, and Professional Services.

Method is part of GlobalLogic, a digital product engineering company. GlobalLogic integrates experience design and complex engineering to help our clients imagine what’s possible and accelerate their transition into tomorrow’s digital businesses. GlobalLogic is a Hitachi Group Company.

About This Opportunity

This is a proactive posting to help us build our network of talented contractors for anticipated project needs later this year. While we don’t have an active project for this role today, we expect opportunities to arise as our client and project needs evolve.

By applying, you’ll be considered for future contract and project-based opportunities that align with your skills, experience, and areas of expertise. Our Talent team will review your background and keep your information on hand, and we’ll reach out directly if an upcoming project looks like a strong match.

Because these opportunities are project-based, timing, scope, duration, and hours may vary depending on the specific engagement. For this type of work, we typically anticipate hourly rates in the range of $79-$120/hour, depending on the project scope, required expertise, and experience level. Specific project details and the applicable rate will be discussed with you when we connect about a potential opportunity.

About Our Team

Our Web Engineering team is made up of seasoned builders who thrive embedded alongside our clients, turning ambiguous problems into working software fast. This is a hybrid of three things we value deeply: the range of a full-stack engineer, the client instincts of a consultant, and the judgment to apply AI where it genuinely moves the needle. You will sit close to the problem, often inside a client's team, translating messy real-world needs into shipped products — and you'll bring modern AI capabilities to bear both in what you build and in how you build it.

We generally operate with small teams working closely together on a wide variety of projects that range from an apparel design studio in the browser, to offline-enabled mobile web applications, to AI-native products that put large language models in front of real users. We have products in production today built with a range of platforms. We are not religious about our technology but choose the best solution for the problem at hand. Our web stack today includes React, Angular, Vue.js, Next.js, TypeScript, Ruby on Rails, Node.js, .NET, and Go, and our AI work spans the major model providers, orchestration frameworks, and retrieval and evaluation tooling.

As a forward deployed engineer, you are comfortable operating in the gray. You go where the problem is — sometimes with a clean brief, more often without one — and you're energized by discovery, ambiguity, and short feedback loops. You can stand in front of a client one hour, discovering what they actually need, and be shipping a working slice of it the next. You know when to reach for AI to accelerate a solution and, just as importantly, when not to.

You are a human first, a developer second. You are willing and able to partake in and lead communication with project stakeholders. You should be able to explain technical constraints — and the capabilities and limits of AI — to both technical and non-technical audiences.

Key Responsibilities

• Embed directly with client teams to discover, scope, and deliver full-stack applications, owning problems end to end from ambiguous brief to production.
• Design, develop, and deploy scalable web applications across the stack using React, Next.js, TypeScript, and modern back-end frameworks and cloud platforms.
• Identify, prototype, and productionize AI-enabled features — including LLM integration, retrieval-augmented generation (RAG), agentic workflows, and intelligent automation — with appropriate evaluation, guardrails, and cost/latency awareness.
• Use AI-assisted development tooling to raise your own and the team's delivery velocity without compromising code quality.
• Implement infrastructure-as-code and automated deployment pipelines to ensure solutions are reliable, observable, and scalable.
• Develop and maintain high-quality automated tests — including evaluation harnesses for AI features — to ensure robustness and reliability.
• Perform thorough code reviews, advocate for best practices, and maintain high engineering standards in fast-moving, client-facing environments.
• Offer technical leadership and mentorship, lifting the AI and full-stack fluency of the teams and clients you work alongside.
• Manage delivery expectations directly with client stakeholders, balancing speed, quality, and scope in real time.
• Keep pace with a rapidly evolving AI and web landscape, forming points of view on where new tools and models create real leverage.

Nice to have

• Experience taking an AI feature from prototype to production, including monitoring, evaluation, and iteration once real users are in the loop.
• Experience building and managing scaled frontend architectures like microfrontends, monorepos, and shared internal libraries.
• Experience managing and evolving CI/CD pipelines and related DevOps tools.
• Experience building authentication and protected applications.
• Experience utilizing tools to support monitoring, logging, and securing applications — including AI observability.
• Experience architecting complex software systems.
• Experience fine-tuning, distilling, or otherwise customizing models, and a point of view on when that's warranted versus prompting or retrieval.

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