Infrastructure Engineer (AWS/ML) - Delivery Consultant, Software Engineering Solutions

Relha LLC; Gilbert, Northern (AZ, KY); Hybrid; USD 110,000 - 160,000; Full time

Job summary

Deloitte US Delivery Center seeks an Infrastructure Engineer (AWS/ML) to operationalize ML in AWS environments and collaborate across data, infra, and application teams. The role emphasizes production support, CI/CD, and secure, scalable platform operations.

You will deploy and monitor ML workloads, manage endpoints and model lifecycles, and work within a hybrid delivery model with travel up to 10% as required.

Qualifications

• 2+ years hands-on AWS, DevOps and infrastructure experience.
• Experience deploying and supporting ML pipelines and production models.
• Ability to travel up to 10% as needed.

Responsibilities

• Build and maintain AWS environments supporting analytics and ML workloads.
• Support ML pipeline engineering, including CI/CD and infrastructure as code.
• Deploy and manage ML models in production with versioning and rollbacks.
• Provide production support: logging, monitoring, incident response and tuning.
• Collaborate with infrastructure, data engineering, and data science teams.

Skills

AWS

DevOps

Infrastructure

Tools

Python

SQL

Job description

Infrastructure Engineer (AWS/ML) - Delivery Consultant, Software Engineering Solutions

Our Deloitte AI & Engineering team to transform technology platforms, drive innovation, and help make a significant impact on our clients’ success. You’ll work alongside talented professionals reimagining and reengineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.

Work You’ll Do

As a US Delivery Center Consultant - Infrastructure Engineer on the team, you will:

You will help operationalize and support the machine learning lifecycle in AWS-based environments. You will work with data engineering, data science, infrastructure, and application teams to deploy, manage, monitor, and support production ML solutions.

You will:

Build and maintain AWS environments supporting analytics and ML workloads, including compute, storage, IAM, VPCs, security groups, SageMaker, Glue, Athena, CloudTrail, and CloudWatch

Support ML pipeline engineering, including Git workflows, CI/CD, infrastructure as code, containerization, and deployment automation

Deploy and manage ML models in production, including endpoints, model versioning, rollback procedures, and release controls

Support MLflow-enabled experiment tracking and model lifecycle management

Execute shadow testing and parallel-run validation to compare new models or pipelines with current-state solutions, identify drift, and assess production readiness

Stand up and maintain research and production environments for analytics and ML pipelines

Implement secure data access, environment configuration, deployment readiness, and operational controls

Provide production support through logging, alerting, incident response, root-cause analysis, job recovery, troubleshooting, and performance tuning

Troubleshoot basic AWS networking, platform, and deployment issues

Embed security, access, and compliance controls into platform operations and deployment processes

Collaborate across infrastructure, application, data engineering, and data science teams while maintaining ownership of assigned deliverables and platform reliability

Document technical processes, operating procedures, deployment standards, and support requirements

The Team

Deloitte’s Government & Public Services (GPS) practice – our people, ideas, technology and outcomes – is designed for impact. Serving federal, state, & local government clients as well as public higher education institutions, our team of professionals brings fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise.

Our Engineering as a Service offering provides end-to-end design, implementation, and technology operations, leveraging our core engineering expertise. We help transform engineering teams, modernize technology, & deliver complex programs with a product engineering mindset. Our flexible delivery models— traditional teams, pools, or pods, are tailored for each client’s needs, offering engineering-led Advise, Implement, & Operate capabilities to accelerate innovation.

This opportunity sits within our Deloitte US Delivery Center model, which is dedicated to driving impactful business services. It leverages Deloitte’s scale and talent, as well as a center delivery model to provide high-quality, cost-effective service with standardized processes and procedures to service businesses across Deloitte.

The Deloitte US Delivery Center has a small-business feel with a big-business impact. With the resources of Deloitte and a community feel, the delivery center model provides high-quality services to our clients. USDC professionals work out of one of our specific delivery center locations, and each location presents dynamic career opportunities for professionals to focus on their work with nominal travel requirements.

Qualifications

Required:

• 2+ years of hands-on AWS, DevOps, and infrastructure experience


• 2+ years of experience developing with Python and SQL

Experience deploying and supporting ML pipelines and production models, including monitoring, troubleshooting, versioning, rollback, and release management

Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future

Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve

Delivery Center Location & Travel Requirements:

Hybrid Work Model: Operate under a hybrid system requiring residence within a commutable distance to one of the US Delivery Center locations (Gilbert, Lake Mary or Mechanicsburg)

Co-location Expectation: Spend up to 30% of working time co-located at an assigned office for orchestrated opportunities, including projects, practice sessions, training, and Moments That Matter at a Deloitte Delivery Center location, Geo-Hub location, approved site, or project location

Travel Requirement: Maximum of 10% overnight travel for client or project purposes

Relocation Requirement: If relocation is necessary, complete the move within 12 weeks from the start date to reside within a commutable distance

Preferred:

Strong written and verbal communication skills, with the ability to explain technical issues to both engineering and business stakeholders.

Hands on AWS experience - compute, storage, IAM, VPC/networking, security groups, SageMaker, Glue, Athena, CloudTrail, CloudWatch, IaaC, and environment management

Experience implementing DevOps / pipeline engineering: CI/CD, GitHub, infrastructure as code, containerization, deployment automation on AWS

Deloitte is committed to providing reasonable accommodations for people with disabilities. If you require a reasonable accommodation to participate in the recruiting process, please direct your inquiries to the Global Call Center (GCC) at [emailprotected] .

Our people and culture

Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ways of thinking, ideas, and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work.

Our purpose

Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Learn more.

From entry-level employees to senior leaders, we believe there’s always room to learn. We offer opportunities to build new skills, take on leadership opportunities and connect and grow through mentorship. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career.

As used in this posting, "Deloitte" means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see https://www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte LLP and its subsidiaries.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.