Senior Principal - AI Engineering

Slalom; Nashville (TN); On-site; USD 198,000 - 247,000; Full time

Benefits offered by this job

401(k) with match

Health, dental, & vision coverage

Adoption and fertility assistance

Disability insurance

Well-being reimbursement account

Job summary

Slalom is seeking an AI/ML Architect to design and deliver production-grade AI systems spanning data, retrieval, orchestration, and deployment across AWS, Azure, and Google Cloud. You will guide strategy, set secure architectures, and move AI solutions from experiments into reliable business operations.

You will lead cross-functional teams of data and ML engineers, drive responsible AI practices, and mentor practitioners.

Qualifications

• 9+ years of experience implementing ML/AI solutions in production.
• 5+ years in professional consulting or IT services leading client engagements.
• Ability to design and govern production AI systems across models, data, orchestration, APIs, security, observability, and UX.
• Deep GenAI patterns: advanced RAG, embeddings, vector/hybrid search, knowledge graphs.
• Experience defining agentic AI architecture patterns and workflows.
• Proficiency with modern AI engineering frameworks and tools listed above.
• Strong Python programming and modern software engineering practices.
• Experience with cloud AI/ML platforms (Bedrock, SageMaker, Vertex AI) and data ecosystems.
• Experience with Databricks, Snowflake, Spark, Kafka, dbt, vector databases.
• Experience setting MLOps/CI/CD, model/versioning, observability, Kubernetes.
• Ability to communicate complex AI concepts to executives.

Responsibilities

• Set technical direction for enterprise-scale AI systems across data products, retrieval pipelines, model orchestration, and AGI workflows.
• Define secure, cloud-native architectures across AWS, Azure, and Google Cloud with modern AI platform services.
• Guide AI strategy and delivery, including generative, agentic, multimodal AI and knowledge assistants.
• Lead production GenAI adoption and tool calling, prompts, memory patterns, and governance controls.
• Establish AI evaluation, observability, and reliability standards with automated evals and tracing.
• Champion Responsible AI, privacy, bias mitigation, and compliance alignment.
• Evaluate emerging models and platforms with executive-ready recommendations.
• Lead cross-functional teams of data/AI engineers, ML engineers, and architects.
• Drive business development with client pitches, accelerators, and reference architectures.
• Develop senior practitioners and a culture of continuous learning in AI practice.

Skills

Production ML/AI

GenAI patterns

LangChain / LangGraph

Python

Cloud AI platforms

MLOps / CI/CD

Data governance

Stakeholder communication

Leadership / mentoring

Enterprise architecture

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Haystack

CrewAI

Hugging Face

Job description

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.

What You’ll Do

• 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.

What You’ll Bring

• 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 LangChain, LangGraph, LlamaIndex, Semantic Kernel, Haystack, CrewAI, Hugging Face, or comparable open-source and cloud-native frameworks.
• Strong programming skills in Python and modern software engineering practices, with familiarity in APIs, event-driven patterns, test automation, infrastructure as code, and scalable service design.
• Proficiency in cloud AI/ML platforms and services such as Amazon Bedrock, AWS SageMaker, Azure AI Foundry, Azure Machine Learning, Google Vertex AI, and related model hosting, retrieval, agent, and evaluation capabilities.
• Experience with enterprise data and AI ecosystems such as Databricks, Snowflake, Spark, Kafka, dbt, vector databases, lakehouse architectures, and modern data governance patterns.
• Experience setting standards for MLOps, LLMOps, CI/CD, model and prompt versioning, automated evaluation, observability, containerization, Kubernetes, serverless deployment, and cost/performance optimization.
• Strong understanding of AI architecture tradeoffs, including model selection, retrieval strategy, latency, accuracy, security, privacy, scalability, cost, vendor lock-in, and operating model implications.
• Ability to communicate complex AI concepts to technical and non-technical stakeholders, translating architecture choices into business value, delivery risk, governance requirements, and executive-level decisions.
• Experience managing senior delivery teams and shaping enterprise AI/ML roadmaps, reference architectures, implementation backlogs, governance models, and adoption plans for enterprise clients.
• Strong problem-solving, critical thinking, and business acumen, with the judgment to distinguish viable production solutions from prototype-only patterns and to guide clients through tradeoffs pragmatically.

About Us

Slalom is a fiercely human business and technology consulting company that leads with outcomes to bring more value, in all ways, always. From strategy through delivery, our agile teams across 52 offices in 12 countries partner with clients to co-create powerful customer experiences, modern ways of working, and meaningful impact.

Compensation and Benefits

Slalom prides itself on helping team members thrive in their work and life. As a result, Slalom is proud to invest in benefits that includemeaningful time off and paid holidays, parental leave, 401(k) with a match, a range of choices for highly subsidized health, dental, & vision coverage, adoption and fertility assistance, and short/long-term disability. We also offer yearly $350 reimbursement account for any well-being-related expenses, as well as discounted home, auto, and pet insurance.

Slalom is committed to fair and equitable compensation practices.For this role, we are hiring at the following levels and targeted base pay salary ranges: The targeted base salary pay range forSenior Principalis $198,000 to $247,000. In addition, individuals may be eligible for an annual discretionary bonus . Actual compensation will depend upon an individual’s skills, experience, qualifications, location, and other relevant factors. The salary pay range is subject to change and may be modified at any time.

Wearecommittedtopaytransparencyandcompliancewithapplicablelaws.Ifyouhavequestionsorconcernsaboutthepayrangeorothercompensationinformationinthisposting,pleasecontactusat: [e-mail]. Pleasenote,thisrecipientisnotabletosupportrecruitmentinquiriesbeyondthispurpose.

EEO and Accommodations

Slalomisanequalopportunityemployerandiscommittedtoattracting,developingandretaininghighlyqualifiedtalentwhoempowerourinnovativeteamsthroughuniqueperspectivesandexperiences.Allqualifiedapplicantswillreceiveconsiderationforemploymentwithoutregardtorace,color,religion,sex,nationalorigin,disabilitystatus,protectedveterans’status,oranyothercharacteristicprotectedbyfederal,state,orlocallaws.Slalomwillalsoconsiderqualifiedapplicationswithcriminalhistories,consistentwithlegalrequirements.Slalomwelcomesandencouragesapplicationsfromindividualswithdisabilities.Reasonableaccommodationsareavailableforcandidatesduringallaspectsoftheselectionprocess.Pleaseadvisethetalentacquisitionteamorcontact [e-mail] ifyourequireaccommodationsduringtheinterviewprocess.