AI Native Data and Knowledge Architect - Senior Manager
$144,000 - $374,000 per year
Apply (opens in a new tab)AI Native Data and Knowledge Architect - Senior Manager
Posted today
SENIORITY
Manager
SALARY
$144,000 - $374,000 per year
About the role
- Set the knowledge direction. Own the target architecture, roadmap, and decision principles for the knowledge, retrieval, and grounding capabilities used by AI products and agents.
- Design organizational memory. Create a federated approach that respects domain ownership while establishing shared meaning, durable interfaces, and clear lifecycle expectations.
- Translate business questions. Work with domain experts to define the concepts, relationships, and boundaries that AI systems need to interpret information accurately.
- Engineer trusted ingestion. Shape reusable patterns that bring varied sources into the platform while preserving authority, lineage, freshness, licensing, and uncertainty.
- Build effective retrieval. Combine search, semantic, graph, and structured methods based on the problem, making relevance, latency, cost, and explainability trade‐offs visible.
- Make evidence inspectable. Ensure context includes citations, provenance, quality signals, and evaluation hooks so users and teams can understand why an answer should be trusted.
- Embed policy in the path. Partner with security, privacy, records, and legal teams to make permitted use, access, retention, and deletion requirements technically enforceable.
- Prove the architecture. Lead lighthouse implementations from prototype through production, using working systems to resolve choices and establish a credible path to scale.
- Operate and improve. Define service objectives, observability, incident learning, and quality measures that keep knowledge capabilities current and dependable after launch.
- Build shared capability. Create reference components and onboarding practices, mentor engineers and stewards, and guide cross‐functional architecture decisions.
- Skills and attributes for success
- Information architecture: Deep understanding of domain modeling, semantics, taxonomies, ontologies, knowledge graphs, and the judgment to choose the simplest durable approach.
- Retrieval expertise: Strong command of search relevance, hybrid retrieval, ranking, grounded generation, context design, and evaluation.
- Data engineering depth: Ability to design reliable pipelines and contracts across enterprise data, documents, events, and operational systems.
- Trust by design: Practical knowledge of provenance, quality, access, privacy, regional, retention, and lifecycle requirements in production systems.
- Product mindset: Ability to connect architecture choices to user outcomes, adoption, operability, and the economics of knowledge workloads.
- Influential leadership: Clear communication and facilitation skills, with the ability to align domain owners, engineers, risk teams, and senior leaders around complex trade‐offs.
- To qualify you must have
- Bachelor's Degree in a relevant field of study.9-12+ years of relevant experience.
- Substantial experience in data, information, solution, or platform architecture, including ownership of production AI, search, or knowledge systems.
- Enterprise delivery: A record of delivering a shared knowledge, search, graph, or grounded‐AI capability across varied sources and organizational boundaries.
- Hands‐on technical depth: Practical fluency with semantic, graph, or retrieval technologies, strong SQL, and a general‐purpose programming language.
- Data integration: Experience designing pipelines that connect analytical, document, event, and operational information with clear production controls.
- Policy‐aware architecture: Evidence of implementing access, provenance, quality, and lifecycle controls through the production retrieval path.
- Architecture judgment: The ability to use prototypes and operational evidence to make sound trade‐offs rather than defaulting to a particular vendor or pattern.
- Cross‐functional leadership: Experience guiding complex decisions and raising engineering capability through influence, collaboration, and mentoring.
- Travel and On‐site requirements: This role requires up to 50% travel and flexibility to go into the office in a hybrid capacity.
- Ideally, you'll also have
- Regulated environments: Delivery experience where residency, retention, confidentiality, or assurance requirements materially shape the architecture.
- Complex knowledge domains: Experience with multilingual or multimodal knowledge, large graphs or indexes, federated query, or fast‐changing information.
- Production scale: Experience balancing relevance, freshness, latency, resilience, and cost for high‐volume knowledge workloads.
- Evaluation expertise: Experience designing meaningful measures for retrieval quality, groundedness, citation accuracy, and authorization behavior.
- Industry contribution: Practical contributions to semantic, data, interoperability, AI operations, open‐source, research, or standards communities.
- We welcome exceptional candidates from product, service design, operations, transformation, policy, domain, and entrepreneurial backgrounds; no particular degree or certification is required.
- What we offer you
- At EY, we harness our collective strength to empower you to shape your future with confidence through professional growth, personal fulfillment and an inclusive culture. Learn more at ey.com/us/careers.
- We offer a comprehensive compensation and benefits package where you'll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job is:
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
