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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive expertise in designing and building knowledge graphs, retrieval architectures, and access control systems within multi-tenant environments. Proven ability to lead technical direction and collaborate across teams in an Agile engineering context.
Highest-signal resume keywords
Knowledge Graph DesignRAG Architecture ExpertiseAccess Control And RBAC DesignAPI And SDK DevelopmentData Governance And Lineage
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringData Layer InfrastructureSearch And Retrieval SystemsVector DatabasesEmbedding-Based RetrievalPythonJavaTechnical LeadershipArchitecture DesignCode Review
Soft Skills
Excellent CommunicationCollaborationInclusive TeamworkAgile Methodology
Industry Keywords
Data GovernanceAuditability RequirementsMulti-Tenant EnvironmentsEnterprise ContextsTechnical Standards
Tech Stack
Tools & technologiesJavaPython
About the role
Key responsibilities & impact- Embed with feature teams to understand context-layer data needs and drive the platform roadmap
- Build the technical vision and roadmap for the AI Context Layer, including knowledge graphs, RAG engines, and retrieval/search infrastructure
- Design and own access control and RBAC for multi-tenant data, agent identity, and fine-grained permissions
- Define and evolve APIs, SDKs, and developer interfaces for the Context Layer
- Identify data platform dependencies and collaborate with data engineering on reliable infrastructure
- Drive architecture discussions, design reviews, code reviews, and technical standards
- Address data access, lineage, governance, security, and auditability requirements
- Contribute to hiring, internal documentation, onboarding, and platform adoption
- Provide cross-cutting technical leadership, roadmap synthesis, and coordination across platform domains
Requirements
What you’ll need- 12+ years of professional software engineering experience, with a strong focus on data-layer or search/retrieval infrastructure
- Proven experience designing and building knowledge graphs and/or large-scale retrieval and search systems in production
- Deep expertise in RAG architectures, vector databases, and embedding-based retrieval, including evaluation, quality tuning, and relevance optimization
- Strong understanding of access control and RBAC design in multi-tenant, data-rich environments
- Experience designing developer-facing APIs and SDKs, with a track record of building intuitive, well-adopted interfaces
- Familiarity with data governance, lineage, and auditability requirements, particularly in enterprise or regulated contexts
- Demonstrated ability to lead technical direction across multiple teams and drive complex, multi-stakeholder projects to delivery
- Experience with Python and/or Java; comfort working across data engineering, backend systems, and platform infrastructure
- Excellent communication skills across engineering, product, data, and leadership
- Ability to work in an inclusive, collaborative, Agile engineering environment