Field Engineer

Who is Recruiting from Scratch : Recruiting from Scratch is a premier talent firm that focuses on placing the best product managers, software, and hardware talent at innovative companies. Our team is 100% remote and we work with teams across the United States to help them hire. AI Field Engineer – AI Natives Location New York, NY / San Mateo, CA / Remote, USA US-based role with the option to work remotely or from the New York or San Mateo office. Compensation $176,000 – $228,000 OTE (80% Base / 20% Variable) + Meaningful Equity Visa Open to H-1B transfers and TN visa sponsorship. O-1 sponsorship considered on a case-by-case basis. Company Stage Growth-Stage / Series C AI Infrastructure Company Industry Artificial Intelligence, Generative AI, Machine Learning, AI Infrastructure, LLMs, Developer Infrastructure, Enterprise Software, B2B SaaS, Cloud Computing, GPU Infrastructure About the Company Our client is building a high-performance AI infrastructure platform that enables companies to build, tune, and scale production AI applications using open models. The platform provides production-grade inference infrastructure, model serving, fine-tuning, evaluation capabilities, and enterprise integrations designed to help AI-native companies move from experimentation to production quickly. The company powers production AI workloads for leading technology companies and AI-native organizations, supporting demanding use cases that require high performance, low latency, reliability, and significant inference scale. The company was founded by engineers and AI infrastructure leaders from some of the world's leading technology organizations and has built a highly technical culture centered around open models, production AI systems, and rapid innovation. The AI Field Engineering team is a small, high-velocity group focused specifically on working with ambitious AI-native customers. The team operates with extreme ownership and expects engineers to combine deep technical expertise with strong customer-facing and product instincts. As an AI Field Engineer, you'll embed directly with AI-native customers to solve complex AI infrastructure problems, build proof-of-concepts and production integrations, and help customers move rapidly from prototype to production. This is a highly technical, customer-facing engineering role where you'll operate at the intersection of engineering, product, and customer delivery. You'll be expected to work directly with customers early in your tenure, own technical engagements end-to-end, contribute production code internally, and translate customer learnings into improvements to the broader platform. What You'll Do Work directly with ambitious AI-native customers to solve complex AI infrastructure and application problems Act as a technical partner to customers from initial discovery through production deployment Build proof-of-concepts, MVPs, and production AI integrations Design and implement production-grade AI systems using open-source models Work hands-on with LLM inference, model serving, fine-tuning, and AI application infrastructure Help customers evaluate and deploy open models for production workloads Develop customer-specific technical solutions across inference, model serving, fine-tuning, and deployment Work closely with customer engineering teams to understand their architecture and technical requirements Translate complex customer requirements into reliable technical solutions Participate in executive-level customer conversations around architecture, strategy, and business outcomes Explain highly technical AI infrastructure concepts clearly to engineering and executive stakeholders Partner with account executives and customer engineering teams throughout technical engagements Own customer technical projects from initial scoping through implementation and production deployment Build and ship production-quality code rather than operating solely in an advisory capacity Contribute directly to internal codebases and platform improvements Translate customer feedback and field learnings into concrete product improvements Work closely with product and engineering teams to influence platform direction Identify recurring customer problems and develop reusable technical solutions Build integrations that can scale across multiple customers and use cases Work with modern LLM serving frameworks such as vLLM, SGLang, and TensorRT-LLM Work with GPU infrastructure and high-performance AI workloads Design and optimize inference systems for latency, throughput, reliability, and cost Work with Kubernetes and modern cloud infrastructure Deploy AI systems across AWS, Azure, and GCP environments Work with enterprise AI platforms including AWS Bedrock, AWS SageMaker, GCP Vertex AI, and Azure AI Foundry Support customers implementing model fine-tuning workflows including SFT, DPO, and RFT Help customers develop evaluation strategies for production AI systems Work with customers to understand model performance and production AI quality requirements Help customers move AI workloads from experimentation into production environments Rapidly learn new customer architectures, technical environments, and AI use cases Operate across engineering, product, infrastructure, and customer-facing responsibilities Work on multiple high-priority customer engagements in parallel Context-switch rapidly between different technical problems and customer environments Operate with high urgency and strong ownership in a fast-moving AI company Make independent technical decisions in ambiguous situations Become client-facing within the first weeks of joining the team Take responsibility for customer outcomes rather than simply providing technical recommendations Help establish repeatable field engineering patterns and technical deployment practices Contribute to the long-term product and technical strategy through customer insights Ideal Candidate Background Experience Requirements 4–10+ years of experience in software engineering, AI/ML engineering, applied AI, solutions engineering, forward deployed engineering, or similar technical roles preferred Strong software engineering background with significant hands-on coding experience Experience building and deploying AI/ML systems in production Experience working with LLMs and generative AI systems Experience building AI-powered applications or infrastructure Experience working directly with customers, clients, or technical stakeholders preferred Experience owning technical projects from discovery through production Experience operating in fast-moving, ambiguous environments Experience working across engineering, product, and customer-facing responsibilities Strong experience with Python Experience with modern cloud infrastructure and distributed systems Experience working with open-source models or AI infrastructure preferred Experience working with AI inference or model serving preferred Experience with production AI workloads preferred Experience at AI-native startups, high-growth technology companies, or similarly demanding environments preferred Demonstrated ability to independently solve complex technical problems Strong ownership mentality with a track record of shipping meaningful technical projects Ability to move quickly from customer problem to working technical solution Experience communicating technical concepts to both engineers and business stakeholders Strong builder mentality and willingness to work outside narrowly defined engineering responsibilities Technical Requirements Strong software engineering fundamentals Strong Python development experience Experience building production AI/ML systems Strong understanding of LLMs and generative AI Experience working with open-source AI models preferred Experience with LLM inference and model serving Familiarity with vLLM, SGLang, TensorRT-LLM, or similar inference frameworks Experience with GPU infrastructure and accelerated computing preferred Understanding of model serving architecture and inference optimization Experience with Kubernetes or similar container orchestration platforms Strong cloud infrastructure experience Experience with AWS, Azure, GCP, or similar cloud platforms Familiarity with AWS Bedrock, AWS SageMaker, GCP Vertex AI, or Azure AI Foundry preferred Experience designing and deploying scalable AI systems Understanding of latency, throughput, concurrency, reliability, and cost optimization Experience working with distributed systems and production infrastructure Experience with APIs and backend application architecture Experience building production-grade AI integrations Familiarity with LLM fine-tuning workflows such as SFT, DPO, or RFT preferred Understanding of AI evaluation and model performance measurement Experience working with production AI observability and reliability considerations preferred Ability to debug complex AI and infrastructure systems Ability to understand unfamiliar technical architectures quickly Ability to rapidly prototype and iterate on technical solutions Strong system design and technical architecture capabilities Ability to translate ambiguous customer requirements into production-ready systems Strong understanding of software engineering best practices Comfortable working across application, infrastructure, model, and deployment layers Ability to make pragmatic technical trade-offs based on customer and business requirements Strong technical judgment around customer-specific implementations versus reusable platform capabilities Education Bachelor's degree preferred Computer Science, Engineering, Mathematics, or equivalent technical disciplines preferred Strong technical or quantitative academic background preferred Exceptional practical engineering experience can compensate for academic pedigree Soft Skills Extremely high agency and ownership Strong bias toward action Highly curious and intellectually engaged Comfortable operating independently Strong builder mentality Deep technical curiosity Passionate about AI and emerging technologies Comfortable working directly with customers Strong customer empathy Comfortable communicating with technical and executive stakeholders Strong interpersonal and communication skills Excellent problem-solving ability Comfortable working through ambiguity Fast learner Strong technical judgment High intensity and urgency Comfortable taking responsibility for customer outcomes Strong product intuition Strong business judgment Able to translate customer problems into technical solutions Comfortable balancing customer requirements with scalable technical architecture Comfortable switching rapidly between different technical problems Comfortable working across engineering, product, and customer-facing responsibilities Comfortable receiving direct customer feedback Willing to iterate quickly based on customer needs Low-ego and highly collaborative Strong team orientation Comfortable working with highly technical customers Comfortable participating in executive-level conversations Excited by working with AI-native companies Excited by open-source AI models and modern AI infrastructure Hungry to learn and build Comfortable operating in a flat, high-trust environment Comfortable with minimal hand-holding Comfortable working in a small, high-velocity engineering organization Strong sense of urgency and accountability Excited by building new systems and solving novel AI problems Compensation & Benefits OTE: $220,000 – $285,000 80% base salary / 20% variable compensation Variable compensation paid quarterly Meaningful competitive equity package Opportunity to work directly with leading AI-native companies Opportunity to solve complex production AI infrastructure problems Exposure to cutting-edge open-source models and AI infrastructure Work with high-performance inference and GPU infrastructure Opportunity to build production AI systems from POC through deployment High degree of technical ownership and autonomy Opportunity to contribute directly to internal platform and product development Opportunity to influence product direction through customer feedback Remote-friendly US-based work environment Option to work from New York City or San Mateo offices H-1B transfer and TN sponsorship available O-1 sponsorship considered case-by-case Performance-based variable compensation Why Join This is an opportunity to join a high-growth AI infrastructure company operating at the center of the rapidly expanding open-model ecosystem. As an AI Field Engineer, you'll work directly with some of the most ambitious AI-native companies in the industry, helping them solve difficult technical problems and move AI systems from experimentation into production. You'll have unusually broad technical ownership. Rather than simply advising customers, you'll build POCs, develop production integrations, work directly with engineering teams, participate in executive conversations, and contribute code back into the core platform. The role sits at the intersection of AI infrastructure, software engineering, product development, and customer delivery. You'll work with modern inference frameworks, GPU infrastructure, cloud platforms, fine-tuning systems, and production LLM workloads while continuously learning from real-world AI deployments. You'll also have a direct product feedback loop. Customer problems won't simply stay in the field — you'll help translate recurring technical challenges into platform improvements and reusable capabilities. If you enjoy deep technical work, production AI systems, open-source models, customer-facing engineering, rapid problem-solving, and operating with extreme ownership, this role offers exceptional scope and impact.