Agentic AI/Machine Learning Architect - Senior Principal
Job in
Atlanta, Fulton County, Georgia, 30383, USA
Listed on 2026-09-01
Listing for:
Slalom
Full Time
position Listed on 2026-09-01
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Description & How to Apply Below
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.
- Set technical direction for enterprise-scale AI systems spanning data products, retrieval pipelines, model orchestration, agentic workflows, evaluation, deployment, monitoring, optimization, and lifecycle management.
- Define secure, scalable, cloud-native and hybrid reference 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.
- Guide applied AI strategy and delivery across generative AI, agentic AI, multimodal AI, advanced RAG, knowledge assistants, prediction, optimization, computer vision, and decision-support use cases.
- Lead enterprise adoption of production GenAI and agentic AI, including advanced RAG, tool/function calling, structured outputs, workflow orchestration, model routing, prompt and context engineering, memory patterns, and human-in-the-loop controls.
- Establish AI evaluation, observability, and reliability standards, including offline test sets, automated evals, tracing, hallucination detection, quality scoring, latency/cost monitoring, feedback loops, and regression testing.
- Champion Responsible AI, AI security, and governance-by-design practices, including explainability, privacy, bias mitigation, guardrails, data protection, threat modeling, access controls, auditability, and compliance alignment.
- Evaluate emerging models, platforms, frameworks, standards, and deployment patterns, providing executive‑ready 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 consistent quality across complex programs.
- Drive business development through proposals, executive client pitches, solution accelerators, reference architectures, technical points of view, and thought leadership.
- Develop senior practitioners and practice capability, fostering a culture of continuous learning, engineering discipline, responsible innovation, and practical AI adoption across the AI/ML practice.
- Help to hire, lead, mentor, and retain a high‑performing, inclusive team of AI/ML engineers, architects, and data scientists. Set clear expectations, provide timely feedback, and create meaningful development and stretch opportunities.
- 9+ years of experience implementing ML/AI solutions in production, including classical ML, deep learning, generative AI, or agentic AI systems.
- 5+ years of experience in professional consulting or IT services, with proven ability to lead complex client‑facing technical engagements.
- Proven ability to design and govern production AI systems that combine models, data, retrieval, orchestration, APIs, security controls, observability, operating model, and user experience into an end‑to‑end enterprise architecture.
- Deep expertise in 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 defining agentic AI architecture patterns, including single‑agent and multi‑agent workflows, supervisor/worker patterns, state and memory management, workflow orchestration, human approval gates, and safe action execution.
- Proficiency with modern AI engineering frameworks and tools such as Lang Chain, Lang Graph, Llama…
Position Requirements
10+ Years
work experience
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