AI Engineer – Enterprise

This is a fully remote position, open to applicants in California.

📋 Description

• Facilitate technical discovery sessions with enterprise clients to comprehend business goals, deployment needs, and success metrics.

• Define and implement proof-of-concepts, pilot programs, and initiatives for production deployment.

• Perform load testing and assessments to affirm model architectures and deployment setups.

• Craft and execute comprehensive AI solutions within intricate enterprise settings.

• Develop production-ready AI and machine learning systems that comply with enterprise standards for performance, security, and regulations.

• Conduct evaluations of models, benchmarking, and performance assessments.

• Guide customers on strategies for model selection and deployment architectures.

• Assist with fine-tuning methods, including Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Reinforcement Fine-Tuning (RFT).

• Create evaluation frameworks to assess model quality and its impact on business.

• Design scalable inference architectures capable of accommodating enterprise workloads.

• Engage with GPU infrastructure, containerized applications, Kubernetes, and cloud platforms.

• Work collaboratively with customer engineering teams to enhance system reliability, latency, scalability, and performance.

• Tackle infrastructure, security, and compliance issues to ensure effective production deployments.

• Provide technical recommendations to engineering teams and executive management.

• Establish trusted relationships with customer stakeholders, identify champions, address concerns, and facilitate successful deployments.

• Recognize recurring customer difficulties and offer constructive feedback to internal product and engineering teams.

• Shape product roadmap decisions through customer insights and field experiences.

⛳️ Requirements

• 4–8 years of experience in AI Engineering, Applied AI, Machine Learning Engineering, Infrastructure Engineering, Field Engineering, Solutions Architecture, or a comparable technical position.

• 3+ years of experience in customer-facing AI/ML or infrastructure roles, with a demonstrated history of leading technical initiatives for enterprise clients.

• Proficient in Python development.

• Proven record of deploying production AI or machine learning systems in enterprise settings.

• Practical experience with Large Language Models (LLMs), open-model inference frameworks, and contemporary model-serving stacks.

• Experience in supporting model training, evaluation, and fine-tuning processes, including SFT, DPO, and RFT.

• Strong knowledge of cloud platforms such as AWS, Azure, or GCP, along with hands-on experience in Kubernetes and containerized environments.

• Experience with GPUs, distributed systems, performance-sensitive infrastructure, and AI infrastructure products and platforms.

• Familiarity with Retrieval-Augmented Generation (RAG) architectures.

• Excellent communication skills, capable of engaging both technical and executive audiences.

• Ability to navigate uncertainty, resolve complex technical issues, and maintain a customer-focused approach with strong business insights.

• Demonstrated executive presence, able to engage thoroughly with engineers while effectively communicating technical trade-offs to senior leadership.

• Experience in customer-facing engineering, field engineering, or solutions architecture roles.

• Experience transitioning enterprise AI solutions from proof-of-concept to production.

• Experience influencing product strategy through customer interaction.

• Background in a startup or rapidly growing technology company, with the ability to excel in fast-paced environments where speed, sound judgment, and ownership are paramount.

🏝️ Benefits

• Competitive salary and performance-based incentives.

• Comprehensive health, dental, and vision insurance.

• Generous paid time off and flexible work arrangements.

• Opportunities for professional development and continuous learning.

• Supportive and dynamic work culture focused on innovation and teamwork.