Associate Consultant - AI Engineering

The AI Engineering Academy is Slalom's structured hiring and onboarding program for early-career engineers. Designed for the AI-native era of consulting, the Academy is an intensive learning program that prepares you to contribute to real client work confidently. During the Academy you will:

• Complete a four-week, immersive training bootcamp covering Slalom consulting foundations,product engineering and project delivery fundamentals, and AI-enabled engineering standards
• Earn hyperscaler and partner certifications (AWS,GCP,Azureand others) that accelerate your readiness for deployment
• Shadow experienced engineers on live engagements, putting your learning into practice on real work
• Build a cohort community with fellow early-career engineers across the US and Canada

At Slalom, we co-create custom software, data, and cloud products with clients who seek all of the benefits of modern, digital products. We're passionate about technology and compelled by its potential — building digital products, experiences, and technology-driven organizations that drive true change. We're driven by the opportunity to build the future we want to see, with anyone willing to join us.

As an Engineer joining our Americas Engineering organization, you will work with our Cloud-Build and Data teams, delivering modern engineering work powered by AI. Our engineering teams span across all engineering domains and cover the full stack — and as an AI Academy hire, you will grow your craft across domains as you develop into a well-rounded, AI-native technology consultant.

Once you complete the academy learning program, you will be deployed to client engagements and grow into a versatile, AI-native engineer across Slalom's Cloud-Build and Data capabilities. Your day-to-day work will span engineering disciplines as you build toward your areas of strength. You will:

• Write high-quality application code, data pipelines, or infrastructure-as-code for cloud-based ecosystems (AWS, Azure, GCP), using AI-assisted tooling and copilots as a core part of how you build
• Own the build and verification of software components at the unit and integration level, applying automated testing as a standard practice rather than an afterthought
• Contribute to data platform delivery, including cloud data warehouses, streaming systems, and AI-accelerated pipelines
• Configure andmaintainthe cloud infrastructure, CI/CD pipelines, and Dev Ops tooling your team depends on
• Drive quality engineering practices, including test planning, automation, and defect management, with an eye toward where AI can accelerate the work
• Partner with senior engineers, architects, and client stakeholders in cross-functional teams, and show up prepared for client-facing ceremonies like stand-ups, sprint reviews, and technical discussions
• Bring whatyou'relearning back to the broader engineering community through knowledge-sharing forums and internal collaboration, helping shape how Slalom builds with AI

We're hiring for potential, curiosity, and consulting aptitude alongside technical fundamentals. You don't need deep specialization yet — you need the right foundation and the mindset to grow fast in an AI-enabled delivery environment.

• Exposure to software development in one or more modern languages (e.g., Python, Type Script, Java, .NET)
• Familiarity with cloud platforms (AWS, GCPor Azure) at a conceptual or hands-on level
• Basic understanding of data concepts — databases, pipelines, or analytics
• Awareness of software quality principles — testing, debugging, or automation
• Academic background and/or experience with AI/ML, GenAI tooling, or intelligent systems
• Demonstrated certification in one or more of the following: AWS, Google, Microsoft, OpenAI, or Anthropic — with preference given to recent AI-focused certifications

• Clear communicator — you can explain your thinking to technical and non-technical audiences
• Client presence — professional, curious, and comfortable in collaborative environments
• Structured problem-solver — you break big problems into smaller ones and…