AI DevOps Engineer (AWS)

Capco; Orlando (FL); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical, Dental, and Vision coverage

401(k) with company match

Health Savings Account (HSA)

Job summary

Capco is seeking an experienced AI DevOps Engineer (AWS) to design, build, and operate scalable cloud infrastructure powering AI and Generative AI capabilities for financial services.

You will enable AI engineers and data scientists to deploy, scale, and secure models, implement IaC, CI/CD, and observability, and collaborate with cross-functional teams to improve platform reliability and cost efficiency.

Qualifications

• 5–7 years of experience in DevOps, Cloud/Platform/SRE with a relevant degree.
• Strong hands-on AWS, IaC (Terraform preferred), CI/CD tooling, Docker, Kubernetes, Linux, and networking fundamentals.
• Experience with AI/ML data platforms or MLOps, plus scripting in Python and/or Bash.

Responsibilities

• Design, build, and maintain scalable AWS infrastructure for AI/ML platforms.
• Develop Infrastructure as Code and automated CI/CD pipelines for AI apps and services.
• Deploy and optimize containerized workloads with Docker and Kubernetes (EKS preferred).
• Implement monitoring, logging, security, and governance across cloud environments.
• Collaborate with AI/ML engineers and data scientists to improve platform reliability and cost efficiency.

Skills

AWS

Terraform

CI/CD

Docker

Kubernetes

Linux

Python

Bash

Education

Bachelor's degree in CS/Engineering/IS

Tools

CloudWatch

Prometheus

Grafana

Datadog

Splunk

Job description

Build the cloud platforms powering the next generation of AI innovation.

The Role

Capco is looking for an experienced AI DevOps Engineer (AWS) to help design, build, and operate the cloud infrastructure that powers our Artificial Intelligence and Generative AI capabilities. Working within our Technology & Engineering Practice, you will enable AI Engineers and Data Scientists to deploy, scale, and manage AI solutions securely, reliably, and efficiently.

This is a senior individual contributor opportunity for someone who enjoys hands‑on engineering, automation, cloud‑native technologies, and solving complex platform challenges while working alongside multidisciplinary teams delivering innovative solutions for leading financial institutions.

What You’ll Do

• Design, build, and maintain scalable AWS cloud infrastructure supporting AI, Machine Learning, and Generative AI platforms.
• Develop Infrastructure as Code using Terraform (preferred), AWS CloudFormation, or equivalent technologies while building automated CI/CD pipelines for AI applications and services.
• Deploy, manage, and optimize containerized workloads using Docker and Kubernetes (Amazon EKS preferred), supporting AI model deployment and lifecycle management.
• Implement monitoring, logging, observability, security, and governance across cloud environments while optimizing reliability, scalability, performance, and cost efficiency.
• Collaborate with AI Engineers, Data Scientists, Data Engineers, and Solution Architects to continuously improve platform engineering, automation, and operational excellence.

What We’re Looking For

• 5–7 years of experience in DevOps, Cloud Engineering, Platform Engineering, or Site Reliability Engineering, supported by a Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
• Strong hands‑on experience with AWS cloud services, Infrastructure as Code (Terraform preferred), CI/CD tooling, Docker, Kubernetes, Linux administration, and cloud networking fundamentals.
• Experience supporting AI, Machine Learning, data platforms, or MLOps environments, with strong scripting skills in Python and/or Bash.
• Experience implementing monitoring, observability, IAM, secrets management, cloud security, governance, and operational best practices using tools such as CloudWatch, Prometheus, Grafana, Datadog, or Splunk.
• Strong troubleshooting, communication, collaboration, and stakeholder engagement skills with the ability to work effectively across cross‑functional engineering teams.

Bonus Points For

• Experience with Microsoft Azure and/or Google Cloud Platform.
• Experience supporting Generative AI, Large Language Models (LLMs), MLOps, MLflow, SageMaker, Kubeflow, or similar technologies.
• Familiarity with vector databases, AI inference platforms, or modern model deployment architectures.
• Experience working within Financial Services or other highly regulated industries.
• AWS Certified DevOps Engineer – Professional, AWS Solutions Architect, or Azure/Google Cloud certifications.

Why Join Capco

• Deliver high‑impact technology solutions for Tier 1 financial institutions.
• Work in a collaborative, flat, and entrepreneurial consulting culture.
• Access continuous learning, training, and industry certifications.
• Be part of a team shaping the future of digital financial services.
• Help shape the future of digital transformation across Financial Services and Energy.
• Medical, Dental, and Vision coverage.
• 401(k) with company match, Health Savings Account (HSA), Flexible Spending Account (FSA), and commuter benefits.
• Maternity and paternity leave, dependent care support, and tuition reimbursement.
• Wellness reimbursement and Working Advantage employee discount marketplace.
• A people‑first culture focused on continuous learning, career growth, and professional development.

Inclusion at Capco

We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.

Use of Artificial Intelligence in Talent Acquisition

At Capco, we use artificial intelligence (AI) tools to support and enhance several parts of talent acquisition. This includes using AI-enabled features within LinkedIn to help source potential candidates, speeding up routine recruitment communications such as emails and creating compelling and brand-aligned job postings that accurately reflect role requirements, and AI-scheduling applications to improve the efficiency of interview coordination.

AI is used as a support tool only. All hiring decisions are made by talent acquisition and hiring teams.

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