Agentic AI / Machine Learning Architect - Senior Principal

Slalom Build; New York (NY); On-site; USD 200,000 - 275,000; Full time

Benefits offered by this job

Annual discretionary bonus

401(k) with a match

Health, dental, and vision coverage

Job summary

Slalom is seeking an AI/ML Architect to design and deliver production-grade AI systems across AWS, Azure, and Google Cloud. You will partner with clients to shape strategy, define secure architectures, and move AI solutions from experimentation into reliable business operations.

You will lead cross-functional delivery teams, champion Responsible AI, and drive governance, security, and cost optimization across complex programs for enterprise clients.

Qualifications

• 9+ years of experience implementing ML/AI solutions in production.
• ,
• ,
• ],
• job_responsibilities_description":[{
• :
• ] ,
• CoT_job_summary_short
• job_summary_short

Responsibilities

• 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 Bedrock, 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, CV, and decision-support use cases.
• Lead enterprise adoption of production GenAI and agentic AI with advanced RAG, tool/function calling, structured outputs, workflow orchestration, model routing, prompts, memory, and human-in-the-loop controls.
• Establish AI evaluation, observability, reliability standards, including offline test sets, automated evals, tracing, hallucination detection, quality scoring, latency/cost monitoring, feedback loops, regression testing.
• Champion Responsible AI, AI security, governance-by-design with explainability, privacy, bias mitigation, guardrails, data protection, threat modeling, access controls, auditability, compliance.
• Evaluate emerging models/frameworks/deployment patterns and provide executive-ready recommendations based on fit, readiness, cost and risk.
• Lead and mentor cross-functional delivery teams of data engineers, AI engineers, ML engineers, software engineers, architects, and consultants.

Skills

Python

GenAI

LangChain

LLM/Ops

APIs

MLOps

Data engineering

AI architectures

Knowledge graphs

Multimodal AI

Tools

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.

What sets us apart? We believe work should be challenging and fulfilling, not perfect, but possible. That’s why we prioritize purpose, flexibility, connection, and recognition, so our people can thrive and love what they do, most days.

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:

For Boston, New York, Washington D.C.:

The targeted base salary pay range for a Sr. Principal is $215,000 to $275,000.

For Atlanta, Charlotte, Philadelphia, Miami:

The targeted base salary pay range for a Sr. Principal is $200,000 to $250,000.

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.

EEO and Accommodations

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

If you're using NVDA, press NVDA key + space to enable focus mode to read the slider properly.