Description and Requirements

Job Description

Who You'll Work With

As a Principal Architect 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

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 include meaningful 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 salary ranges:

• East Bay, San Francisco, Silicon Valley:
  • Senior Principal: $229,000-$281,000
• Boston, Los Angeles, New Jersey, New York City, Orange County, San Diego, Seattle, Washington DC, White Plains:
  • Senior Principal: $210,000-$257,000
• All other locations:
  • Senior Principal: $193,000-$236,000

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 pay range is subject to change and may be modified at any time.

We will accept applicants until the position is filled.