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HR POD - Hiring Talent Globally

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AI Engineer – Enterprise

AI EngineerMachine Learning EngineerFull TimeRemoteSeniorTeam 11-50Since 2023H1B No SponsorCompany SiteLinkedIn

Location

California

Posted

1 day ago

Salary

0

Seniority

Senior

Job Description

AI Engineer – Enterprise

HR POD - Hiring Talent Globally

• Lead technical discovery sessions with enterprise customers to understand business objectives, deployment requirements, and success criteria. • Scope and execute proof-of-concepts, pilot programs, and production deployment initiatives. • Conduct load testing and evaluations to validate model architectures and deployment configurations. • Design and implement end-to-end AI solutions within complex enterprise environments. • Build production-grade AI and machine learning systems that meet enterprise performance, security, and compliance requirements. • Conduct model evaluations, benchmarking, and performance testing. • Advise customers on model selection strategies and deployment architectures. • Support fine-tuning methodologies, including Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Reinforcement Fine-Tuning (RFT). • Develop evaluation frameworks to measure model quality and business impact. • Design scalable inference architectures that support enterprise workloads. • Work with GPU infrastructure, containerized applications, Kubernetes, and cloud platforms. • Collaborate with customer engineering teams to optimize system reliability, latency, scalability, and performance. • Address infrastructure, security, and compliance challenges to ensure successful production deployments. • Present technical recommendations to engineering teams and executive leadership. • Build trusted relationships with customer stakeholders, identify champions, address objections, and drive successful deployments. • Identify recurring customer pain points and provide actionable feedback to internal product and engineering teams. • Influence product roadmap decisions through customer insights and field experience.

Job Requirements

  • 4–8 years of experience in AI Engineering, Applied AI, Machine Learning Engineering, Infrastructure Engineering, Field Engineering, Solutions Architecture, or a similar technical role.
  • 3+ years of experience in customer-facing AI/ML or infrastructure roles, with a proven track record of leading technical workstreams for enterprise customers.
  • Strong Python development experience.
  • Proven experience deploying production AI or machine learning systems in enterprise environments.
  • Hands-on experience with Large Language Models (LLMs), open-model inference frameworks, and modern model-serving stacks.
  • Experience supporting model training, evaluation, and fine-tuning workflows, including SFT, DPO, and RFT.
  • Strong understanding of cloud platforms, including AWS, Azure, or GCP, with hands-on experience in Kubernetes and containerized environments.
  • Experience working with GPUs, distributed systems, performance-critical infrastructure, and AI infrastructure products and platforms.
  • Knowledge of Retrieval-Augmented Generation (RAG) architectures.
  • Strong communication skills, with the ability to engage both technical and executive audiences.
  • Ability to navigate ambiguity, solve complex technical challenges, and maintain a customer-centric mindset with strong business acumen.
  • Demonstrated executive presence, with the ability to engage deeply with engineers while clearly communicating technical trade-offs to senior leadership.
  • Experience working in customer-facing engineering, field engineering, or solutions architecture roles.
  • Experience deploying enterprise AI solutions and taking AI solutions from proof-of-concept to production.
  • Experience influencing product strategy through customer engagement.
  • Experience working in a startup or high-growth technology company, with the ability to thrive in fast-paced environments where speed, sound judgment, and ownership are essential.

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