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SRE (AI/ML)

Kforce Technology StaffingMaryland Heights, MO🇺🇸United StatesPosted 31 Aug 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Maryland Heights, MO, United States
Posted
23 hours ago
AWSMLOpsSnowflakeAzureBashCDKCloudFormationDatabricksKubernetesLESSLLMPythonRedshiftTerraform

Job Description

RESPONSIBILITIES

Kforce has a client in Maryland Heights, MO that is seeking a SRE (AI/ML) with hands-on AI/ML engineering experience to design, operate, and scale reliable cloud platforms that power production AI/ML and GenAI workloads.

Summary

The SRE will own reliability, automation, and cost/performance of AWS infrastructure while partnering with data science and application teams to productionize models, ML pipelines, and LLM/RAG solutions. The role blends classic SRE and cloud administration with modern MLOps and LLMOps practices.

REQUIREMENTS

  • 8+ years total experience with at least 3+ years as SRE/DevOps/Cloud Admin on AWS in production
  • Strong hands-on with core AWS services: EC2, VPC, IAM, S3, RDS, EKS/ECS, Lambda, CloudWatch, CloudTrail
  • Proficient in Python and one of Bash; comfortable writing reusable modules and operational tooling
  • Solid IaC experience with Terraform (preferred) and/or CloudFormation/CDK
  • Kubernetes (EKS) in production: workloads, autoscaling, networking (CNI), and secrets
  • Working knowledge of ML lifecycle: data prep, training, evaluation, deployment, and monitoring
  • Hands-on with at least one of: SageMaker, Bedrock, Vertex AI, or Azure ML in production
  • Experience operating LLM/GenAI or classical ML services with observability and guardrails
  • Strong incident management, on-call, and postmortem culture experience

Nice to have

  • AWS certifications: Solutions Architect Professional, DevOps Engineer Professional, Security Specialty, or ML Specialty
  • Experience with LangChain, LlamaIndex, Strands, or agentic frameworks in regulated environments
  • Vector databases and retrieval tuning (hybrid search, re-ranking, chunking strategies)
  • Model governance, responsible AI, PII/PCI handling, and audit-ready ML pipelines
  • Exposure to Databricks, Snowflake, Redshift or Iceberg-based lakehouses
  • GPU/accelerator experience (A10/A100/H100, Inferentia/Trainium) and cost-aware inference design

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

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