Agentic AI - Sr. Principal - Intelligence Engineering (US)

Who You’ll Work With
At Slalom, we co-create modern technology and software products with clients who are ready to accelerate their digital product development. We imagine how things can be made better, then set out to realize what’s possible—driving innovation with quality, resilience, and purpose. By blending design, product engineering, analytics, and automation, we build the custom-built software and data products of tomorrow. As a Senior Principal in Intelligence Engineering, you will define, design, and lead the delivery of enterprise-scale AI/ML and agentic AI solutions, shaping how intelligent systems are built, deployed, and scaled across organizations. You will operate at the intersection of strategy and execution—guiding architectural direction while remaining hands-on in building critical components.
You’ll partner with clients to move from early experimentation to production-grade intelligent systems, establishing patterns for scalability, reliability, and governance, while helping shape Slalom’s broader AI strategy and capabilities.

We offer a flexible working environment to balance the need to work independently, with some days that may require in-person collaboration at our office.

What You’ll Do
Define and lead end-to-end architecture for agentic AI systems, including multi-agent designs, planning loops, memory strategies, and tool orchestration
Establish reference architectures and reusable patterns for AI/ML and GenAI systems across clients and internal teams
Design scalable ML and agent pipelines, including CI/CD, observability, evaluation frameworks, and production deployment strategies
Architect enterprise-grade AI platforms that integrate LLMs, RAG systems, structured data systems, and external tools
Lead design and implementation of Model Context Protocol (MCP) integrations and cross-system interoperability
Act as the primary technical authority and trusted advisor for clients, leading architecture discussions and shaping technical strategy
Translate ambiguous business needs into clear, scalable, and production-ready technical solutions
Lead technical discovery, solution design, and early-stage project definition, influencing scope and delivery approach
Guide clients in evolving from POCs to enterprise-scale systems, ensuring performance, reliability, and governance
Remain deeply hands-on (~60–75%), building critical components such as:
RAG pipelines, agent orchestration systems, and APIs
Evaluation frameworks and observability tooling
ML/LLM pipelines and production services
Work across AWS, Azure, and GCP, selecting the right combination of cloud-native AI and data services
Build in Python and related technologies, contributing directly to complex system components
Lead small, high-performing teams (3–7 engineers) as the technical lead from inception through delivery
Mentor engineers and architects, elevating team capability in AI, architecture, and engineering practices
Set engineering standards and best practices for AI system development, testing, and deployment
Define and implement AI governance frameworks, including model risk management, safety, and compliance
Establish guardrails, HITL workflows, and monitoring systems for autonomous decision-making
Ensure systems meet standards for security, observability, scalability, and performance
Contribute to Slalom’s Intelligence Engineering strategy, helping define offerings, accelerators, and best practices
Provide thought leadership in AI/ML, GenAI, and agentic systems, both internally and with clients
Lead technical workshops, architecture reviews, and strategic conversations with executive stakeholders
Drive innovation and capability building across the broader practice

What You’ll Bring
8+ years of software engineering experience building and deploying production systems, with deep expertise in AI/ML or intelligent systems
3+ years of experience designing and delivering GenAI, LLM, or agentic AI systems at scale
Proven experience owning end-to-end architecture for complex distributed systems, including ML pipelines, APIs, and cloud infrastructure
Hands-on expertise with multi-agent systems, orchestration frameworks (LangGraph, AutoGen, CrewAI, Semantic Kernel, OpenAI Agents SDK, etc.), and autonomous workflows
Deep experience with RAG architectures, including vector databases, embeddings, retrieval strategies, and context management
Strong experience designing production-grade ML/LLM pipelines, including CI/CD, observability, evaluation, and monitoring (MLOps/LLMOps)
Experience building solutions on at least one major cloud platform (AWS, Azure, or GCP) with a strong understanding of architecture trade-offs
Strong Python development skills, including APIs (FastAPI/Flask) and system integration
Experience designing evaluation frameworks and measurement strategies for GenAI systems (e.g., RAGAS, LangSmith, DeepEval)
Demonstrated ability to act as a technical leader and client-facing architect, with excellent communication and stakeholder management skills
Recognized as a subject matter expert in one or more areas (e.g., Agentic AI, RAG systems, AI architecture)
Ability to lead in ambiguous environments, define direction, and drive alignment across technical and business stakeholders
Preferred:
Experience with Model Context Protocol (MCP) development and integration
Experience designing enterprise AI governance frameworks
Exposure to responsible AI practices and regulatory considerations

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 peop