AI​/ML Architect - Principal; US - EAST

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* Please note:

This role isnot eligible for
100% remote work. Employees must live within a commutable distance of a Slalom Office and must be willing to be onsite at the client and/or Slalom office when needed up to 3 days a week. ****

At Slalom, we co-create modern technology and software products with clients who are accelerating their digital transformation journeys. We blend design, product engineering, analytics, automation, and AI-native delivery to build intelligent products and platforms that can operate safely at enterprise scale. As an AI/ML Architect, you’ll design and deliver production-grade AI systems that combine machine learning, generative AI, agentic workflows, modern data platforms, and cloud-native engineering across AWS, Azure, and Google Cloud.

You’ll partner with clients to shape strategy, define secure and governed architectures, and move AI solutions from experimentation into reliable business operations.

• Architect and deliver enterprise-scale AI systems spanning data products, retrieval pipelines, model orchestration, agentic workflows, evaluation, deployment, monitoring, optimization, and lifecycle management.
• Design secure, scalable, cloud-native and hybrid architectures across AWS, Azure, and Google Cloud, including modern AI platform services such as Amazon Bedrock, Azure AI Foundry, Google Vertex AI, and enterprise data platforms.
• Lead applied AI solution design across generative AI, agentic AI, multimodal AI, advanced RAG, knowledge assistants, prediction, optimization, computer vision, and decision-support use cases.
• Enable production GenAI and agentic AI adoption, including advanced RAG, tool/function calling, structured outputs, workflow orchestration, model routing, prompt and context engineering, memory patterns, and human-in-the-loop controls.
• Define AI evaluation, observability, and reliability patterns, including offline test sets, automated evals, tracing, hallucination detection, quality scoring, latency/cost monitoring, feedback loops, and regression testing.
• Champion Responsible AI and AI security practices, including governance, explainability, privacy, bias mitigation, guardrails, data protection, threat modeling, access controls, auditability, and compliance-by-design.
• Evaluate emerging models, platforms, frameworks, standards, and deployment patterns, providing practical recommendations based on use case fit, enterprise readiness, cost, risk, and operational complexity.
• Lead and mentor cross-functional delivery teams of data engineers, AI engineers, ML engineers, software engineers, architects, and consultants, ensuring on-time, high-quality outcomes.
• Support business development through proposals, client pitches, solution accelerators, reference architectures, technical points of view, and thought leadership.
• Coach and mentor junior consultants, fostering a culture of continuous learning, engineering discipline, responsible innovation, and practical AI adoption across the AI/ML practice.

• 6+ years of experience implementing ML/AI solutions in production, including classical ML, deep learning, generative AI, or agentic AI systems.
• 3+ years of experience in professional consulting or IT services, with proven ability to lead client-facing technical engagements.
• Hands-on experience designing production AI systems that combine models, data, retrieval, orchestration, APIs, security controls, observability, and user experience into an end-to-end architecture.
• Deep understanding of modern GenAI patterns, including advanced RAG, embeddings, vector and hybrid search, re-ranking, knowledge graphs, tool/function calling, structured outputs, context engineering, and multimodal inputs.
• Experience with agentic AI…