Job Title: AI Field Engineer – AI / ML & Agentic Systems

Location: Remote
Work Mode: Remote-friendly with regular customer travel / on-site customer visits

Employment Type: Full-time permanent role

About the Role

We are looking for an experienced AI Field Engineer who combines strong AI/ML engineering skills with customer-facing technical expertise.

This role sits at the intersection of engineering, product, pre-sales, and customer delivery. You will work directly with customers to understand complex AI requirements, build proofs of concept, develop MVPs, integrate AI systems into production environments, and help customers successfully deploy and optimize AI solutions.

The ideal candidate is highly technical, comfortable writing production code, and equally confident presenting technical solutions to engineering teams, product leaders, and senior stakeholders.

Key Responsibilities

Work directly with customers to understand technical and business requirements.
Build and deliver Proofs of Concept (POCs) and MVPs.
Develop production-ready AI/ML integrations.
Embed and deploy AI solutions within customer environments.
Own customer-facing technical implementations from discovery through production.
Build, maintain, and optimize ML/AI systems.
Support AI model deployment, inference, training, and fine-tuning workflows.
Help customers optimize application and model performance.
Manage technical relationships with customer accounts.
Present architecture, strategy, technical trade-offs, and business outcomes to stakeholders.
Translate customer feedback into product and engineering improvements.
Collaborate closely with product teams to rapidly improve solutions based on customer needs.
Support enterprise and AI-native customers through fast-moving implementation cycles.
Take significant ownership of technical delivery and customer outcomes.

Required Technical Skills

Candidates should have strong experience with:

Python
Machine Learning
Artificial Intelligence
Large Language Models (LLMs)
Generative AI
Production ML / AI systems
LLM deployment
Model fine-tuning
Model training
Inference optimization
Cloud infrastructure
Production system integration
Customer-facing technical implementation

LLM / GenAI Skills

Strong preference is given to candidates with hands-on experience in:

Supervised Fine-Tuning (SFT)
Direct Preference Optimization (DPO)
Reinforcement Fine-Tuning (RFT) or equivalent methods
LLM training and fine-tuning
Production LLM deployment
GenAI infrastructure
Inference optimization
Open-source models

Experience should go beyond theoretical knowledge or advisory work and include actual implementation and deployment into production environments.

Infrastructure & Deployment Skills

Relevant experience includes:

AWS
Google Cloud Platform
Azure
GPU infrastructure
Kubernetes
Model serving
AI/ML infrastructure
Cloud deployment

Experience with inference-serving frameworks such as:

vLLM
SGLang

is highly valuable.

Client-Facing / Pre-Sales Experience

This role requires genuine customer-facing technical experience.

Candidates should have experience with activities such as:

Running technical discovery sessions
POCs and Proofs of Value
MVP development
Technical workshops
Pre-sales engineering
Solution architecture
Customer implementation
Account technical management
Presenting to technical and executive stakeholders
Embedding code into customer environments
Owning technical customer relationships

Candidates must combine both AI/ML technical depth and client-facing experience.

Eligibility Criteria

Candidates should have:

3–10 years of relevant professional experience.
Preferably 5+ years for senior profiles.
Experience in a customer-facing technical AI/ML role.
Strong software engineering ability.
Strong Python skills.
Proven experience building and shipping production AI/ML systems.
Experience developing systems from the ground up.
Direct experience running POCs or MVPs.
Experience presenting technical solutions to stakeholders.
Strong understanding of LLMs and GenAI systems.
Experience with model deployment, fine-tuning, training, or inference.
Ability to manage customer relationships.
Ability to independently own complex technical implementations.
Strong communication and presentation skills.
Ability to operate effectively in fast-paced environments.
Comfort with regular on-site customer visits within the U.S.

FTE ( Fulltime role): AI Field Engineer AI / ML & Agentic Systems: Remote

Quick Overview

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