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Machine Learning Operations (MLOps) Architect - Generative Al Focus

6 hours, 14 minutes ago
United States
Full-time
Senior
AI Engineer
DevOps and Infrastructure
AWS CI/CD CloudFormation Databricks Docker Feature Engineering Generative AI Kubernetes LLM MLflow MLOps Python SageMaker Terraform
Apply Now
Kapitus

Kapitus

Kapitus, a leading small business financing company, offers fast, flexible term loans and lines of credit from $5k to $5 million. With a focus on simplifying financing for small businesses, Kapitus provides multiple loan options to support business gro...

Diversified Financial Services
251-1K
Founded 2006
$490M raised
View All Jobs 23

Description

  • Design and implement scalable ML and LLM infrastructure on AWS using services such as SageMaker, EKS, S3, IAM, Lambda, Step Functions, and CloudWatch.
  • Architect end-to-end ML and Generative AI lifecycle workflows from data ingestion and preprocessing through training, fine-tuning, deployment, monitoring, and retraining.
  • Integrate LLM pipelines, including prompt workflows, RAG architectures, and fine-tuning flows, into the enterprise MLOps stack.
  • Define and enforce CI/CD/CT standards across ML and GenAI workloads.
  • Architect Retrieval-Augmented Generation pipelines, including embedding generation, vector database integration, document chunking, and retrieval monitoring.
  • Design and deploy LLM-based services using managed endpoints or containerized custom inference services.
  • Establish prompt versioning, evaluation frameworks, experiment tracking, and guardrails for LLM systems.
  • Implement model monitoring, observability, and traceability standards for performance, drift, output quality, latency, and token usage.
  • Define SLAs/SLOs and safe deployment strategies such as blue/green, canary, and shadow testing.
  • Implement FinOps practices for ML and GenAI workloads, including cost tracking, optimization, forecasting, and autoscaling strategies.
  • Provide architectural guidance to data science, AI, and engineering teams and drive reusable documentation and standards.

Requirements

  • 6+ years of experience in ML engineering, data engineering, or MLOps roles.
  • Proven experience architecting ML platforms in AWS.
  • Strong hands-on experience with SageMaker, including training, pipelines, and deployment.
  • Experience operationalizing LLM or Generative AI systems in production.
  • Experience building RAG pipelines and integrating vector databases.
  • Experience working with Databricks in production.
  • Experience implementing data governance and catalog systems such as Atlan.
  • Strong understanding of CI/CD principles for ML and GenAI.
  • Experience with Docker and Kubernetes/EKS.
  • Deep knowledge of infrastructure as code tools such as Terraform and CloudFormation.
  • Strong understanding of observability and monitoring for ML systems.
  • Experience implementing cloud cost optimization strategies (FinOps).
  • Strong Python proficiency.
  • Experience with foundation model fine-tuning and parameter-efficient methods.
  • Experience implementing model registries and experiment tracking tools.
  • Experience designing feature stores and embedding stores.
  • Familiarity with AI risk management, bias mitigation, and safety controls.
  • Experience supporting regulated or data-sensitive environments.
  • Platform-level architectural thinking and the ability to integrate GenAI into enterprise ML ecosystems.
  • Ability to balance scalability, governance, security, performance, and cost.
  • Strong technical leadership and cross-functional collaboration skills.
  • Hands-on ability to move from architecture design to implementation.

Benefits

  • Competitive base salary range of $117,800 to $189,000, depending on location, skills, and experience.
  • Annual incentive compensation eligibility of up to 10% annually.
  • Comprehensive medical, dental, and employer-paid vision insurance.
  • Flexible spending account for qualified medical, dental, vision, pharmacy, and dependent care expenses.
  • Lifestyle spending account for physical, mental, and financial well-being expenses.
  • 100% company-paid basic short-term and long-term disability insurance, plus vision insurance.
  • Paid maternity and parental leave.
  • Commuter benefits for parking and travel expenses.
  • Tuition reimbursement of up to $5,000 annually, plus conference and career development support.
  • Paid time off and sick time.
  • 401(k) retirement plan with a 25% company match up to 6% of annual salary.
  • Remote candidates may be considered if they reside in eligible states where Kapitus or a subsidiary has a physical presence.

Interested in this position?

Apply directly on the company website

Apply Now

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