Caylent · 2 weeks ago
Principal AI/ML Architect
United States
Full-time
Remote
Lead/Staff
10+ years expCaylent is a cloud native services company that helps organizations leverage technology using Amazon Web Services (AWS). They are seeking a Principal AI/ML Architect to lead client engagements, shape strategy, and provide architectural guidance for machine learning projects, ensuring technical quality and driving business value for customers.
Cloud ComputingCloud InfrastructureDevOpsIaaS
No H1B
Responsibilities
Lead end-to-end ML assessments across infrastructure, data pipelines, model lifecycle, and organizational readiness — producing recommendations that drive executive decision-making and earn Caylent the next engagement
Partner with sales and solutions teams through the proposal and scoping phase, contributing the technical depth needed to shape well-grounded statements of work
Serve as the senior technical authority on client engagements — possibly across multiple projects simultaneously — providing architectural guidance, ensuring technical quality from your project team members, and getting hands-on when the engagement demands it, without owning day-to-day implementation responsibilities
Own or orchestrate high-quality POCs that give customers confidence before committing to a larger initiative
Advise customers on ML operations standards and architecture — covering MLOps pipeline design, model lifecycle management, LLMOps patterns, and production monitoring frameworks — translating operational complexity into decisions and guardrails their teams can own and sustain
Shape how Caylent wins its most technically complex opportunities — contributing the architectural thinking and credibility that turns prospects into customers
Strengthen the ML practice from the inside — through peer guidance, technical interviews, and contributions to accelerators, reference architectures, and thought leadership content
Qualification
Required
10+ years in machine learning or AI, with a proven track record of leading client-facing engagements in a consulting or advisory capacity
Deep, current knowledge of the AWS ML and GenAI ecosystem, with the ability to make and defend architectural decisions across the full ML lifecycle — from data and feature engineering through training, deployment, and monitoring
Deep expertise in at least two or three ML domains — whether traditional ML, computer vision, NLP, time series, or others — combined with the judgment to assess, architect, and advise across the broader ML landscape
Proven ability to architect and govern production ML systems end-to-end, translating MLOps, LLMOps, and broader AI operations complexity into standards and decisions that engineering teams can execute and executives can act on
Deep expertise across foundation model adaptation — fine-tuning (LoRA, QLoRA, PEFT), alignment (RLHF, DPO), inference optimization (quantization, vLLM), and distributed training (DeepSpeed, FSDP) — combined with RAG and agentic system design, including multi-agent architectures, event-driven workflows, MCP integration, and human-in-the-loop patterns on AWS. Technical authority to prescribe the right approach and set architectural standards that teams can execute against
Proven ability to operate independently in complex customer environments — navigating ambiguity, aligning stakeholders, and translating ML tradeoffs into business risk and value for both technical and executive audiences
Preferred
AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect – Professional
Experience shaping practice-level standards, reference architectures, and reusable ML accelerators across multiple engagements
Exposure to varied industries and problem types in a consulting or client-facing context
Deep fluency in responsible AI practices — model evaluation, bias detection, fairness frameworks, and AI governance — applied in enterprise deployments
Hands-on experience designing and deploying SRE agents and AI-driven operations workflows in production — spanning automated incident detection, triage, and remediation — with the ability to integrate across observability platforms and translate AI operations outcomes into measurable business value
Benefits
100% remote work
Private Health Insurance
Flexible Time Off
Competitive phantom equity
Paid for exams and certifications
Peer bonus awards
State of the art laptop and tools
Equipment & Office Stipend
Individual professional development plan
Annual stipend for Learning and Development
Work with an amazing worldwide team and in an incredible corporate culture
Company
Caylent
Caylent is a next-generation cloud services company to adapt with speed and drive intelligent growth by leveraging AI and AWS expertise.
501-1000 employees
Funding
Current Stage
Late StageTotal Funding
$16.31MKey Investors
Gryphon InvestorsEast Los Capital
2022-11-15Private Equity
2022-11-15Acquired
2021-09-27Private Equity· $16M
Leadership Team
Valerie Henderson
Chief Executive Officer
Stephen Garden
Vice Chairman
Recent News
Founder Institute
2026-07-17
Company data provided by crunchbase