Senior MLOps & GenAI Platform Architect

Kapitus; Virginia (MN); On-site; USD 180,000 - 240,000; Full time

Job summary

Kapitus is seeking a Senior MLOps Architect to design and scale a modern ML and Generative AI platform across AWS. You will own the architecture for traditional ML and LLM pipelines, ensuring production reliability, governance, cost optimization, and enterprise-grade security in a large-scale environment.

You will lead end-to-end ML/GenAI workflows, integrate RAG pipelines and vector databases, define CI/CD standards, and enable secure deployment, monitoring, and retraining of models using

Qualifications

• 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 (training, pipelines, deployment).

Responsibilities

• Design and implement scalable ML and LLM infrastructure on AWS (SageMaker, EKS, S3, IAM, Lambda, Step Functions, CloudWatch).
• Architect end-to-end ML and Generative AI lifecycle workflows (data ingestion, feature engineering, model training, evaluation, deployment).
• Integrate LLM pipelines (RAG, prompts) into the enterprise MLOps stack.
• Define CI/CD/CT pipelines across ML and GenAI workloads.
• Establish guardrails for monitoring, governance, cost controls, and security.

Skills

AWS

SageMaker

Databricks

MLOps

GenAI

RAG architectures

Security

FinOps

CI/CD

Kubernetes

Tools

SageMaker

Databricks

EKS

IAM

CloudWatch

Terraform

Job description

Kapitus is seeking a Senior MLOps Architect to design and scale a modern ML and Generative AI platform across AWS. You will own the architecture for traditional ML and LLM pipelines, ensuring production reliability, governance, cost optimization, and enterprise-grade security in a large-scale environment.

You will lead end-to-end ML/GenAI workflows, integrate RAG pipelines and vector databases, define CI/CD standards, and enable secure deployment, monitoring, and retraining of models using