AI/ML Architect - Consultant / Senior Consultant (US - WEST)

Overview In this role you will design, build, and deploy generative AI and ML solutions that address real business problems. You will work within Slalom's Data & AI capability to develop cutting-edge AI tools and collaborate with engineers, data scientists, and AI leaders. You’ll apply LLM-based approaches (RAG, agents, prompt engineering, fine-tuning) and advance production-quality AI implementations with a strong emphasis on validation, observability, and governance. This role offers hands-on influence across client work and internal AI communities, with a clear impact on scalable AI solutions and customer outcomes. You’ll thrive in a collaborative, growth-oriented environment that values practical Compensation / Benefitsmeaningful time off and paid holidaysparential leave 401(k) with matchinghealth, dental, & vision coverageadoption and fertility assistancewell-being reimbursement Responsibilities Design, build, and deploy generative AI and ML solutions to solve business problems Develop LLM-powered applications using RAG, agents, prompt engineering, tool calling, workflow automation, and fine-tuning Apply ML and DL methods to create AI tools for real-world use cases Contribute to design, development, presentation, and delivery of traditional ML solutions (CV, NLP, recommendations)Stay updated on AI/ML fundamentals and trends to inform solution discussions Mentor and share knowledge to grow the AI/ML community within the organization Key requirements 3+ years in production ML/model implementation 2-4 years in professional consulting (Managed or IT)Strong consultative and communication skills for diverse stakeholders Solid technical foundation with curiosity in ML/AIFluency in AI/GenAI, ML, and at least one major cloud (AWS, GCP, Azure)Hands-on experience with generative AI: LLMs, embeddings, vector search, RAG, agents, prompt engineering, fine-tuning Experience with AI validation, observability, and production-grade metrics (accuracy, groundedness, safety, latency, cost, drift)Experience deploying ML/AI into production and discussing best practices and pitfalls Understanding of AI/ML validation frameworks and production-ready offerings Excellent Python skills for ML/AI use cases Data Science and/or Data Engineering background preferredstrong communicationcollaborative mindsetcuriosity and continuous learning Generative AI / LLMsRAG, embeddings, vector searchprompt engineering, fine-tuning