6 days ago
Remote, United StatesStaff+
Base Salary
$152k - $220k/yr
Responsibilities
- Own enterprise architectural strategy and key decisions for designing and scaling Generative AI capabilities.
- Define how enterprise data, knowledge, metadata, and domain structures are organized, governed, versioned, and accessed by AI systems.
- Establish source-to-AI information flows covering curation, indexing, embeddings, retrieval, ranking, and context delivery.
- Define agent framework and orchestration patterns for models, data sources, APIs, downstream systems, tool usage, execution boundaries, and escalation paths.
- Set direction for embedding AI capabilities into customer touchpoints, internal tools, and operational workflows.
- Establish patterns for handling non-deterministic behavior, ambiguity, failures, quality evaluation, and downstream impact.
- Identify fragmentation and drive consolidation into coherent, reusable architectural patterns.
- Direct enterprise practices for prompt injection risk, data leakage, least privilege, auditability, DLP, model risk controls, regulatory expectations, and safe agent use.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
- Ten or more years of experience across data architecture, distributed systems, or enterprise platform design.
- Experience owning architectural direction and influencing system design across multiple teams.
- Strong understanding of structured and unstructured data modeling, governance, and accessibility across complex systems.
- Experience designing large-scale systems integrating data platforms, APIs, and distributed services.
- Practical knowledge of modern data platforms such as Snowflake, including ingestion, transformation, and consumption layers.
- Understanding of retrieval, indexing, and search systems operating at scale.
- Deep familiarity with Generative AI and Agentic AI concepts, including embeddings, retrieval, prompt composition, agent memory, and orchestration.
- Ability to balance performance, scalability, cost, and operational complexity while designing distributed systems.
- Strong understanding of access control, security, and governance in distributed environments.
- Experience with third-party and open-source agent frameworks.
- Preferred experience designing systems where AI outputs drive user actions, decisions, or automated workflows.
- Preferred depth in information retrieval, search systems, knowledge architectures, production safeguards, fallback strategies, and scaling challenges.
- Recognized expertise through targeted certifications in AWS architecture, Snowflake data platforms, or applied machine learning, with demonstrated depth in Generative AI platforms such as AWS Bedrock or equivalent LLM ecosystems.
Benefits
- Medical, dental, vision, and life insurance.
- 401(k) retirement plan with company matching contributions of up to 6%, potential discretionary contribution, financial advisory services, and investment options.
- Tuition reimbursement up to $5,250 per year.
- Generous paid time off upon hire, including paid company holidays and floating holidays.
- Paid volunteer time of 16 hours per calendar year.
- Paid parental leave, paid short- and long-term disability, and Family and Medical Leave programs.
- Business Resource Groups open to all employees.
- Flexible work environment and professional office setting; remote and hybrid workers must provide reliable high-speed wired internet and an appropriate home workspace, and may be required to work in the office if requirements are not met.
Tech Stack
AWSSnowflake
Categories
