AI Field Engineer - AI Natives

Summary

The employer is a growth-stage AI infrastructure company building platforms for production applications using open models. The AI Field Engineer will work directly with AI-native customers to design and deploy AI systems, build proof-of-concepts and production integrations, solve infrastructure challenges, and translate customer feedback into platform improvements.

Responsibilities

• 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

Skills

• * 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 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
• * 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
• * Strong software engineering fundamentals
• * Strong Python development experience
• * Experience building production AI/ML systems
• * Strong understanding of LLMs and generative AI
• * Experience with LLM inference and model serving
• * Familiarity with vLLM, SGLang, TensorRT-LLM, or similar inference frameworks
• * 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
• * 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
• * Understanding of AI evaluation and model performance measurement
• * 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
• * 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
• * 4–10+ years of experience in software engineering, AI/ML engineering, applied AI, solutions engineering, forward deployed engineering, or similar technical roles preferred
• * Experience working directly with customers, clients, or technical stakeholders preferred
• * 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
• * Strong understanding of LLMs and generative AI
• * Experience working with open-source AI models preferred
• * Experience with GPU infrastructure and accelerated computing preferred
• * Familiarity with AWS Bedrock, AWS SageMaker, GCP Vertex AI, or Azure AI Foundry preferred
• * Familiarity with LLM fine-tuning workflows such as SFT, DPO, or RFT preferred
• * Experience working with production AI observability and reliability considerations preferred
• * 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

Qualifications

Must Haves

• * 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 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
• * 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
• * Strong software engineering fundamentals
• * Strong Python development experience
• * Experience building production AI/ML systems
• * Strong understanding of LLMs and generative AI
• * Experience with LLM inference and model serving
• * Familiarity with vLLM, SGLang, TensorRT-LLM, or similar inference frameworks
• * 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
• * 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
• * Understanding of AI evaluation and model performance measurement
• * 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
• * 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

Nice to Haves

• * 4–10+ years of experience in software engineering, AI/ML engineering, applied AI, solutions engineering, forward deployed engineering, or similar technical roles preferred
• * Experience working directly with customers, clients, or technical stakeholders preferred
• * 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
• * Strong understanding of LLMs and generative AI
• * Experience working with open-source AI models preferred
• * Experience with GPU infrastructure and accelerated computing preferred
• * Familiarity with AWS Bedrock, AWS SageMaker, GCP Vertex AI, or Azure AI Foundry preferred
• * Familiarity with LLM fine-tuning workflows such as SFT, DPO, or RFT preferred
• * Experience working with production AI observability and reliability considerations preferred
• * 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

Benefits

• Open to H-1B transfers and TN visa sponsorship.
• Performance-based variable compensation paid quarterly (20% of OTE)
• Meaningful competitive equity package
• Opportunity to work directly with leading AI-native companies
• 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