Infrastructure Engineer; AWS​/ML; Delivery Consultant, Software Engineering Solutions

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.

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.

Build and maintain AWS environments supporting analytics and ML workloads, including compute, storage, IAM, VPCs, security groups, Sage Maker, Glue, Athena, Cloud Trail, and Cloud Watch

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

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

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

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.

• 2+ years of hands-on AWS, Dev Ops, and infrastructure experience
• 2+ years of experience developing with Python and SQL

Experience deploying and supporting ML pipelines and production models, including monitoring, troubleshooting,…