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Forward Deployed Engineer

MLabs

Ubicación
San Francisco, California, United States
Publicado
20 oct 2026

Confirma que la oferta sigue abierta y revisa sus condiciones en el sitio web de la empresa antes de solicitar el puesto.

Descripción del puesto

La interfaz está en español. Los títulos y las descripciones de las empresas se mantienen en el idioma original de publicación, que puede ser inglés.

Location: Hybrid (NYC) - Remote (United States) Compensation: $149K - $185K Our client is a high-growth technology organization building an advanced AI platform designed for enterprise operations and value creation in an AI-native world. Founded by experienced leaders in applied AI and mission-critical infrastructure, the organization leverages a proven track record of developing leading risk management and financial infrastructure that has processed trillions in volume. Backed by top-tier venture capital firms with over $65 million in funding, the company maintains an agile, elite team focused on solving technically ambitious problems. Operating with a culture centered on high-agency, talent-dense individual contributors, our client emphasizes high autonomy, meaningful ownership, and strong judgment over hierarchy. They are seeking a Forward Deployed Engineer to own the technical customer journey and turn complex enterprise challenges into high-value, production-grade AI solutions. In this high-impact role, the successful candidate will bridge technical strategy and customer execution—partnering closely with product, sales, and engineering leaders to guide strategic clients from technical discovery through implementation, production rollout, adoption, and scaling. Key Responsibilities End-to-End AI Deployments: Own strategic client engagements throughout the lifecycle, including technical discovery, scoping, architecture design, hands-on implementation, evaluation, production rollout, and long-term adoption. Pre-Sales & Solution Architecture: Partner with the commercial team during pre-sales phases to lead technical discovery, design tailored AI solutions, and perform validation for high-value customer opportunities. Post-Sales Technical Execution: Drive post-sales success by building and integrating production AI systems that transition clients from initial concept into full production environments. Production AI Systems Engineering: Develop scalable AI applications utilizing modern large language models (LLMs), model APIs, tool calling, retrieval-augmented generation (RAG), context management, structured outputs, and agentic workflows. Product Optimization & Feedback Loops: Translate recurring customer insights into product enhancements—identifying cross-deployment patterns and developing reusable components, playbooks, tooling, and core product features. Proactive Problem Solving: Identify operational and technical opportunities, formulate strong architectural points of view, and execute without requiring rigid direction. Basic Qualifications Experience: 5+ years of experience as a Forward Deployed Engineer, Solutions Engineer, Sales Engineer, Founding Engineer, or Product Engineer with significant end-to-end customer ownership. Execution Track Record: Proven history of taking ambiguous client challenges from initial discovery through to production deployment and measurable business impact. Technical & Commercial Judgment: Strong ability to evaluate trade-offs across client needs, product features, engineering complexity, cost, and latency. Core Technical Stack: Proficiency with Python and/or Rust, React/TypeScript, SQL, APIs, system integrations, authentication protocols, cloud infrastructure, and production observability. AI & LLM Expertise: Hands-on experience building AI-powered applications, including working with model APIs, context management, tool integration, retrieval architectures, model evaluation, and performance optimization. Location & Work Style: Based in the United States or Europe for remote arrangements (NYC-based candidates will work in-office 2–3 days per week). High agency and comfort operating autonomously in fast-paced, ambiguous environments. Preferred Qualifications Travel Flexibility: Ability to travel up to 30% annually for in-person team collaboration and client engagements. Communication: Exceptional written and verbal English communication skills, with the ability to articulate complex technical architecture to both technical and executive audiences. Performance Tuning: Familiarity with profiling tools, optimization techniques, and low-latency system design. Competitive Total Compensation: Base salary range of $149,000 – $185,000, plus a competitive equity package aligned with performance and growth. Career Advancement: Opportunity to play a foundational role within a rapidly growing global technology organization. Workplace Flexibility: Remote options (US/Europe) or hybrid flexibility in New York City.  Interview Process Initial Screening: Introductory conversation to align on background, experience, and role expectations. Technical & Architectural Evaluation: Deep dive into software engineering fundamentals, AI systems architecture, and system design. Behavioral & Scenario-Based Review: Practical discussion focused on client facing scenarios, technical trade-offs, and forward-deployed problem-solving. Final Leadership Alignment: Conversations with key leadership stakeholders across Product, Sales, and Engineering. Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search. Commitment to Equality and Accessibility: At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing human-resources@mlabs.city. MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd’s Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting legal@mlabs.city.

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Elige ejemplos reales de tu experiencia que respondan a los requisitos del puesto. Explica tu aportación y utiliza cifras solo cuando puedas justificarlas. Sigue las instrucciones de la empresa y revisa los datos de contacto, el contenido y el PDF antes de enviar la candidatura.

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Preguntas sobre la búsqueda de empleo

¿Por qué algunas ofertas están en inglés?

Las empresas publican sus propios títulos y descripciones. Conservamos ese texto para no alterar requisitos o condiciones. La navegación y esta guía están en español. Si una búsqueda en español no encuentra ofertas, prueba también el título o la competencia en el idioma del anuncio, por ejemplo «software engineer».

¿Un puesto remoto permite trabajar desde cualquier país?

No necesariamente. La empresa puede limitar los países de residencia, exigir autorización para trabajar o fijar un horario. Comprueba estos puntos en la oferta original. Si no aparecen, consúltalos con la empresa antes de asumir que puedes trabajar desde tu ubicación.

¿Qué hago si no aparecen resultados?

Prueba un título más general o una sola competencia y elimina los filtros de uno en uno. Los nombres de los puestos varían entre empresas. Si una oferta concreta ha desaparecido, busca su referencia en la página de empleo de la empresa; ampliar los filtros no recupera una vacante cerrada.

¿La candidatura se envía desde ResumizeAI?

El botón de solicitud abre un destino externo. Sigue las instrucciones de la empresa o del proveedor de selección y confirma allí el envío. Preparar un currículum en ResumizeAI no equivale a presentar una candidatura. Si el enlace solo abre la web de la empresa, busca la vacante antes de continuar.

¿Cómo adapto el currículum y la carta de presentación?

Relaciona los requisitos con proyectos, tareas y resultados que puedas explicar. Destaca lo relevante sin inventar experiencia ni copiar competencias que no tienes. En la carta, explica tu interés y aporta un ejemplo concreto. Respeta el idioma y el formato pedidos y revisa ambos documentos antes de enviarlos.