Data Products - Member of Technical Staff

Simile • San Francisco, CA

7d

About The Position

Simile is developing an AI simulation of society, using generative agents based on real people to predict human behavior. The Data Products team builds the systems that collect, structure, secure, and make useful the data that powers those simulations. This includes an in-house AI interview platform for real-time, adaptive conversations at scale and infrastructure for securely handling data for enterprise organizations.

In this role, you will bridge AI and production-grade enterprise data systems. You will design and scale products for sensitive, messy, real-world data, building systems that are secure, auditable, and reliable by construction while remaining simple for users. You will own data products from architecture through backend services, APIs, and user-facing workflows, and collaborate with research, product, and enterprise customers to turn ambiguous needs into durable capabilities. You will balance architectural rigor with incremental delivery and learning from real-world usage.

Requirements

• At least 5 years of professional engineering experience, excluding internships, at tech- and product-driven companies.
• Experience owning production systems that customers depend on.
• Strong command of Python and/or TypeScript, with solid SQL and data-modeling fundamentals.
• Experience with relational databases such as Postgres and cloud infrastructure such as AWS, GCP, or Azure.
• Hands-on experience building data pipelines or integrations, including batch and/or streaming processing, workflow orchestration, and schema evolution.
• Practical experience with authentication and authorization, encryption, secrets management, multi-tenancy, and sensitive data in enterprise or regulated environments.
• Ability to balance technical excellence with pragmatic shipping while centering the customer's problem.
• Ability to thrive in a fast-growing environment, navigate loosely defined tasks, and manage competing priorities effectively.

Nice To Haves

• Experience with terabyte- or petabyte-scale datasets and distributed data processing using technologies such as ClickHouse, Flink, or BigQuery.
• Experience with WebRTC, streaming speech-to-text and text-to-speech, or LLM-powered conversational products.
• Experience building customer-facing enterprise connectors, data-sharing workflows, APIs/SDKs, or developer platforms.
• Experience working with sensitive customer data and protecting, de-identifying, and sharing it responsibly.
• Familiarity with SOC 2, HIPAA, GDPR, enterprise security reviews, or privacy-enhancing techniques such as differential privacy.
• Curiosity about social science, survey research, or how people think and make decisions.

Responsibilities

• Own data products from initial architecture through backend services, APIs, and user-facing workflows; make core design decisions about storage, orchestration, and data modeling, including whether to build or buy.
• Build and scale pipelines that gather data from diverse sources, normalize it into consistent formats, and make it available to product and research teams at scale.
• Build systems for secure handling and processing of sensitive data, including PII redaction, tenant isolation, encryption at rest, and appropriate access controls.
• Design flexible integrations for structured and unstructured data from multiple sources and formats, handling schema changes, partial failures, and edge cases without disrupting downstream consumers.
• Partner with researchers, product teams, and enterprise customers to turn ambiguous requirements into durable data capabilities.
• Ship incrementally and balance long-term architectural rigor with learning from real-world usage.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed