AI/ML Engineer (107-10SENG-01)

Role overview A consulting AI/ML Engineer role embedded with North American tech teams to deliver short-cycle proofs of concept and minimum viable products, typically one to eight weeks in length. The work spans generative AI applications, classical machine learning, MLOps infrastructure, and AWS cloud modernization, with each project staffed alongside a Solution Architect and Cloud/Data Engineers.

Responsibilities - Build generative AI applications including retrieval-augmented generation pipelines, agentic workflows, chatbots, voice agents, and integrations with managed model platforms. - Develop classical machine learning solutions such as anomaly detection, forecasting, and recommendation engines. - Deliver MLOps and machine learning infrastructure builds that support model training, deployment, and ongoing operations. - Contribute to AWS data and cloud modernization initiatives including Migration Acceleration Program assessments, QuickSight, and data migrations. - Take proofs of concept and MVPs from initial scoping through delivery within compressed project timelines. - Collaborate closely with a Solution Architect and Cloud/Data Engineers on every engagement.

Requirements - Five or more years of experience as an AI/ML Engineer or in a closely related role. - Deep AWS platform experience across Bedrock, SageMaker, Lambda, VPC, QuickSight, and DynamoDB or S3. - Hands-on generative AI skills including retrieval-augmented generation, agent orchestration, guardrails, and prompt design. - Applied machine learning fundamentals spanning time-series analysis, anomaly detection, and model training and evaluation. - Demonstrated experience with MLOps and ML infrastructure, as well as delivering PoCs and MVPs. - English communication skills at B2 or above, with the ability to work independently in a fast-paced, distributed environment.

Nice to have - Background working inside consulting or professional services delivery models.