Staff Full Stack AI Engineer

We are seeking a highly experienced and versatile Staff ML Engineer to join our dynamic Data & AI team. In this critical role, you will design, develop, and deploy AI applications incorporating sophisticated AI agents capable of complex reasoning, planning, and autonomous action. We're looking for a candidate with hands-on expertise in Python-particularly using LangChain,LlamaIndex, HayStack, AutoGPT-who can architect agentic workflows and integrate complex ETL pipelines. You should be comfortable designing and deploying web app POCs on AWS and orchestrating tooling, APIs and third-party systems to build robust data-driven applications. You will tackle ambiguous problems, provide technical leadership across front-end, back-end, and AI components, and help shape the technical direction for our agentic AI initiatives. This is a unique opportunity to apply your full-stack expertise to the forefront of AI development. Travel for team and client meetings is required, typically up to 15%. Responsibilities: - Work directly within client teams to discover, scope, and deliver full-stack applications, owning problems end-to-end from an 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. Qualifications You will succeed in this role if you have: - Strong, engaging consulting experience and problem-solving skills, with a track record of thriving in ambiguous, client-facing settings. - Track record of ramping quickly on unfamiliar codebases, domains, and client organizations. - 7+ years of experience working on large development projects using React and related tools. - Strong proficiency in programming in TypeScript. - Strong understanding of component lifecycles, hooks, and concurrent features in modern React (18+), including awareness of Server Components and App Router patterns in Next.js. - Strong understanding of state management tools such as Redux, Context, and RTK Query, and their different uses and purposes. - Strong experience building robust unit and component tests with tools such as Jest, Vitest, React Testing Library, and Cypress. - 5+ years of experience building and integrating with REST APIs and back-end services using modern languages and frameworks such as Node.js, .NET, Ruby on Rails, or Go. - Get equally excited about scalable UI and scalable API design. - Hands-on experience with a major cloud platform (Azure, AWS, or GCP) and infrastructure-as-code practices. - Experience architecting complex software systems, owning design decisions and documenting the trade-offs behind them. - Experience setting technical direction beyond a single team, influencing standards and engineering practices across teams or engagements. - 2+ years of hands-on experience building with modern AI, delivered into real products or client engagements. - Practical experience integrating large language models via major provider APIs (e.g., Anthropic, OpenAI, or equivalent). - Familiarity with retrieval-augmented generation (RAG), vector stores, embeddings, and prompt design. - Practical experience with agentic patterns, orchestration frameworks, and tool/function calling, including tool-integration protocols such as MCP. - A working grasp of AI evaluation, guardrails, safety, and the cost-and-latency trade-offs of deploying models in production. - Fluency with AI-assisted development tooling as a force multiplier for delivery. - Client delivery instincts: comfort working deeply integrated with client teams, translating business requirements into technical specifications, and shipping under real-world constraints. - Awareness of how technical decisions affect the scope, timeline, and margin of an engagement. - 3+ years of experience leading an engineering team, mentoring team members, and planning and strategizing work delivery. - Experience working directly with stakeholders to manage delivery expectations. - Work well with others, enjoy collaborating with and mentoring others, and are unafraid to reach out to others for support. - Love learning and growing as much as delivering high-quality products and features. 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 including microfrontends, monorepos, and shared internal libraries. - Experience managing and evolving CI/CD pipelines and related DevOps tools. - Experience building authentication and protected applications. - Experience using tools to support monitoring, logging, and application security - including AI observability. - Experience in 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. We look for individuals who are smart, kind and brave. Curious people with a natural ability to think on their feet, learn fast, and develop points-of-view for a constantly changing world find Method an exciting place to work. Our employees are excited to collaborate with dispersed and diverse teams that bring together the best in thinking and making. We champion the ability to listen, and believe that critique and dissonance lead to better outcomes. We believe everyone has the capacity to lead and look for proactive individuals who can take and give direction, lead by example, enjoy the making as much as they do the thinking, especially at senior and leadership levels. We believe in work/life balance. Seriously. We offer a ton of competitive perks, including: - Continuing education opportunities - Flexible PTO and work-from-home policies - 401K matching - Health, Dental and Vision benefits, starting on day 1 - Company lunches, company outings, along with a lot of snacks - Health and wellness programs - Other location specific perks (just ask!) Next Steps If Method sounds like the place for you, please submit an application. Also, let us know if you have a presence online with a portfolio, GitHub, Dribbble or other platform. Colorado Applicants (Colorado Equal Pay for Equal Work Act Disclosure): The starting salary range for this role to be performed in Colorado is estimated to be between $145,000 to $175,000 annually. This salary range is specific to Colorado residents only, and provided as a general estimate. The amount offered may be higher or lower. Method takes many factors into making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations. New York City Applicants (New York City Local Law 32; Pay Transparency Law): The starting salary range for this role to be performed in New York City is from $160,000 to $190,000. This salary range is specific to New York City residents only, and provided as a general, good faith estimate. The amount offered may be higher or lower. Method takes many factors into making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations.