Job Type

Full-time

Description

Through our Data and AI Practice, we partner with clients to build scalable, reliable data foundations across AWS and Azure. Our focus is on modern data engineering-developing data platforms and pipelines that enable analytics, machine learning, and AI in realworld production environments. We believe strong data engineering is critical to making AI useful, trustworthy, and sustainable.

CSTG consultants combine proven engineering practices with a handson consulting mindset, helping clients move from strategy to implementation while delivering solutions aligned to real business needs.

What does your team look like:

Our teams are highly collaborative and crossfunctional, blending CSTG consultants with client stakeholders to solve complex data challenges. We value engineers who are curious and pragmatic, and who want to "major" in data engineering with a complementary understanding of AI and machine learning to build durable, productionready data solutions.

What does your role look like:

As an AI/ML Engineer in CSTG's Data and AI Practice, you will be a handson contributor supporting the delivery of AI and machinelearning solutions for client engagements. You will work as part of a delivery team to contribute to the development and delivery of AI and machinelearning solutions, including generative AI and agentbased use cases, that are deployed and used as part of client production systems.

AI/ML Engineers focus on execution and growth, applying established techniques, learning best practices for building AI systems, and contributing to solution delivery under the guidance of more senior team members. As a consulting role, this position includes interaction with client stakeholders and requires clear communication and a professional presence.

This role emphasizes skill development, collaboration, and building experience delivering reliable, highquality AI solutions in real world environments.

Responsibilities:

• Contribute to the development and delivery of AI and machine-learning solutions for client engagements, including generative AI and agent-based capabilities.
• Implement AI workflows, services, and integrations that work alongside data and application platforms.
• Apply established AI techniques, patterns, and tools to solve well-defined problems.
• Participate in design discussions, reviews, and team feedback sessions.
• Collaborate with data engineers and application engineers to support production-ready AI solutions.
• Follow responsible AI practices, including awareness of data usage, bias, transparency, and privacy considerations.
• Write clear, maintainable code and supporting documentation.
• Continue developing skills in AI, machine learning, and production delivery practices.

Requirements

• 2+ years of experience building or supporting AI or machinelearning solutions.
• Experience using Python for AI or machine-learning development.
• Familiarity with machine learning, generative AI, or agent-based approaches.
• Experience working with structured or unstructured data for AI use cases.
• Basic understanding of model evaluation, performance considerations, and limitations.
• Exposure to deploying or supporting AI solutions in production or near-production environments.
• Familiarity with AWS and/or Azure services.
• Understanding of foundational data engineering concepts, such as data pipelines and data quality.
• Ability to communicate technical concepts clearly within a team and with client stakeholders.

Preferred Qualifications:

• Experience with LLM platforms or tools such as Amazon Bedrock, Azure AI Foundry, or similar.
• Exposure to MLOps practices, including model versioning or monitoring.
• Experience working alongside data engineering teams on shared solutions.
• AWS, Azure, or entry-level AI/ML certifications.
• Databricks or Snowflake certifications.
• Previous consulting or client-facing experience.

*Must be located in either the Greater Indianapolis Area OR the Greater St. Louis Area OR the Greater Austin, TX Area