Agentic AI Leader - Intelligence Engineering (AI/ML)
Slalom · Seattle, WA
- On site
- Full-time
- $281,000 / year
- Seattle, WA
Job highlights
- Lead AI/ML and agentic AI solution architecture.
- Design scalable AI platforms and pipelines.
- Hands-on development of RAG and agent systems.
- Client-facing technical authority and advisor.
- Mentor teams and set engineering standards.
About the role
Agentic AI Leader - Intelligence Engineering (AI/ML)
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 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 AI 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 Qualifications:
- 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 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 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.
EEO and Accommodations
Slalom is an equal opportunity employer and is committed to attracting, developing and retaining highly qualified talent who empower our innovative teams through unique perspectives and experiences. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veterans’ status, or any other characteristic protected by federal, state, or local laws. Slalom will also consider qualified applications with criminal histories, consistent with legal requirements. Slalom welcomes and encourages applications from individuals with disabilities. Reasonable accommodations are available for candidates during all aspects of the selection process. Please advise the talent acquisition team if you require accommodations during the interview process.
Key skills/competency
- Agentic AI
- Intelligence Engineering
- AI/ML Architecture
- GenAI
- LLM
- RAG Systems
- MLOps/LLMOps
- Python Development
- Cloud Platforms (AWS, Azure, GCP)
- Technical Leadership
Skills & topics
- Agentic AI Leader
- Intelligence Engineering
- AI/ML
- GenAI
- LLM
- RAG
- Machine Learning
- Deep Learning
- Python
- Cloud Architecture
- AWS
- Azure
- GCP
- MLOps
- LLMOps
- Software Engineering
- Technical Lead
- Principal Architect
- Consulting
- Digital Transformation
How to get hired
- Research Slalom's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor to align your application with their 'fiercely human' approach.
- Tailor your resume: Highlight 8+ years of software engineering and 3+ years in GenAI/agentic AI, emphasizing end-to-end architecture, RAG, and multi-agent systems.
- Showcase technical leadership: Detail your experience leading teams, client-facing engagements, and in-depth hands-on development in Python and cloud platforms.
- Prepare for technical interviews: Be ready to discuss complex distributed systems, ML pipelines, MLOps/LLMOps, and architectural trade-offs across AWS, Azure, and GCP.
- Highlight innovation and impact: Demonstrate your ability to translate ambiguous business needs into scalable, production-ready AI solutions and drive client success.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the key responsibilities for an Agentic AI Leader at Slalom?
- As an Agentic AI Leader at Slalom, you will define and lead the architecture for enterprise-scale AI/ML and agentic AI solutions. This includes designing scalable ML and AI pipelines, architecting AI platforms, leading RAG and multi-agent system development, and acting as a trusted technical advisor to clients. You will also be hands-on in building critical components and mentoring engineering teams.
- What experience is required for the Agentic AI Leader role at Slalom?
- The role requires 8+ years of software engineering experience with a focus on AI/ML or intelligent systems, and at least 3 years specifically in designing and delivering GenAI, LLM, or agentic AI systems at scale. Proven experience in end-to-end architecture for complex distributed systems, hands-on expertise with multi-agent systems and RAG architectures, and strong Python development skills are essential.
- What cloud platforms does Slalom work with for AI/ML projects?
- Slalom works across major cloud platforms including AWS, Azure, and GCP. Candidates are expected to have experience building solutions on at least one of these platforms and a strong understanding of architecture trade-offs within them.
- What is the expected hands-on involvement for this Agentic AI Leader position?
- This role is deeply hands-on, with approximately 60-75% of your time dedicated to building critical components. This includes developing RAG pipelines, agent orchestration systems, APIs, evaluation frameworks, observability tooling, and ML/LLM production services.
- What are the salary ranges for the Senior Principal level at Slalom?
- Salary ranges vary by location. For example, in East Bay, San Francisco, and Silicon Valley, the range is $229,000-$281,000. In other major cities like Boston, Los Angeles, and New York City, it's $210,000-$257,000. For all other locations, the range is $193,000-$236,000. An annual discretionary bonus may also be available.
- Does Slalom offer a flexible work environment for this role?
- Yes, Slalom offers a flexible working environment. This allows for balancing independent work with days that may require in-person collaboration at the office.
- How does Slalom approach AI governance and responsible AI?
- Slalom emphasizes defining and implementing AI governance frameworks, including model risk management, safety, and compliance. This involves establishing guardrails, human-in-the-loop (HITL) workflows, and monitoring systems for autonomous decision-making, with a focus on responsible AI practices.
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