[Remote] Principal AI/ML Architect

Note: The job is a remote job and is open to candidates in USA. Caylent 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.ResponsibilitiesLead 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 engagementPartner with sales and solutions teams through the proposal and scoping phase, contributing the technical depth needed to shape well-grounded statements of workServe 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 responsibilitiesOwn or orchestrate high-quality POCs that give customers confidence before committing to a larger initiativeAdvise 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 sustainShape how Caylent wins its most technically complex opportunities — contributing the architectural thinking and credibility that turns prospects into customersStrengthen the ML practice from the inside — through peer guidance, technical interviews, and contributions to accelerators, reference architectures, and thought leadership contentSkills10+ years in machine learning or AI, with a proven track record of leading client-facing engagements in a consulting or advisory capacityDeep, 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 monitoringDeep 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 landscapeProven 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 onDeep 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 againstProven 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 audiencesAWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect – ProfessionalExperience shaping practice-level standards, reference architectures, and reusable ML accelerators across multiple engagementsExposure to varied industries and problem types in a consulting or client-facing contextDeep fluency in responsible AI practices — model evaluation, bias detection, fairness frameworks, and AI governance — applied in enterprise deploymentsHands-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 valueBenefits100% remote workPrivate Health InsuranceFlexible Time OffCompetitive phantom equityPaid for exams and certificationsPeer bonus awardsState of the art laptop and toolsEquipment & Office StipendIndividual professional development planAnnual stipend for Learning and DevelopmentWork with an amazing worldwide team and in an incredible corporate cultureCompany OverviewAWS Premier Partner for Cloud Native Services It was founded in 2015, and is headquartered in Irvine, California, USA, with a workforce of 501-1000 employees. Its website is https://caylent.com.