Clera

<h3>About the Role</h3><p>Build autonomous AI agents designed to handle complex work over extended periods with minimal human intervention. You will own core agent systems, memory, and evaluation, helping improve reliability and establish when agents can outperform people on specific tasks.</p><h3>What You'll Do</h3><ul><li><p>Build agents that can pursue a goal over multiple weeks without human intervention.</p></li><li><p>Design memory systems that help agents retain knowledge and improve over time.</p></li><li><p>Develop evaluations to determine whether agents perform tasks better than the people who previously handled them.</p></li><li><p>Improve agent reliability while reducing the need for human review and oversight.</p></li></ul><h3>What We're Looking For</h3><ul><li><p>Hands-on experience building production agents that people rely on, and a clear understanding of their current limitations.</p></li><li><p>At least 1 to 2 years of experience at a fast-growing or AI-focused startup.</p></li><li><p>Experience building evaluation systems that inform real-world decisions.</p></li><li><p>Evidence of impact through published research others build on or software shipped at meaningful scale.</p></li><li><p>Strong opinions on agent architecture are a plus.</p></li><li><p>Background in competitive math, programming, debate, games, startup founding, or participation in a leading accelerator is valued.</p></li><li><p>Collaborative, kind, and effective communication, including in challenging situations.</p></li></ul><h3>Compensation &amp; Benefits</h3><p>Base salary is $200,000 to $300,000 annually, with up to $350,000 for exceptional candidates. Meaningful founding equity is offered. Visa sponsorship is available.</p><h3>Location</h3><p>On-site, five days a week in San Francisco, California, United States.</p>

Founding Engineer, Agents

<h3>About the Role</h3><p>Build evaluation environments and benchmarks that measure whether AI agents can perform real company work and match or exceed human performance. This founding engineering role focuses on agent capability assessment and production readiness, helping establish reliable evidence of agent competence.</p><h3>What You'll Do</h3><ul><li><p>Design synthetic company environments with realistic emails, records, and files generated from scratch.</p></li><li><p>Build graders and evaluation systems that can assess agents even when their performance may exceed human reviewers' expertise.</p></li><li><p>Develop benchmarks whose rankings correlate with real-world production performance.</p></li><li><p>Find and address evaluation failure modes, including reward hacking and benchmark gaming.</p></li><li><p>Simulate tools such as inboxes and CRMs with enough fidelity to support agent interactions at scale.</p></li></ul><h3>What We're Looking For</h3><ul><li><p>Hands-on research experience with synthetic data pipelines, benchmarks, evaluations, or post-training.</p></li><li><p>At least 1 to 2 years of experience at a fast-growing or AI-focused startup.</p></li><li><p>Experience building environments or benchmarks for frontier AI training or evaluation is valuable.</p></li><li><p>A track record of finding flaws in established benchmarks, improving them, and addressing reward hacking in evaluation systems.</p></li><li><p>Ability to simulate complex software systems that can withstand agent tool use.</p></li><li><p>Startup experience, strong performance in competitive mathematics, programming, debate, or games, and a collaborative approach under pressure are valued.</p></li></ul><h3>Compensation &amp; Benefits</h3><p>Base salary is $200,000 to $300,000 annually, with up to $350,000 for exceptional candidates. A commission-style bonus of up to $200,000 or more is tied to the value of delivered environments. Meaningful founding equity is available. Visa sponsorship is not available.</p><h3>Location</h3><p>On-site five days a week in San Francisco, California, United States.</p>

Founding Engineer, Environments and Data

<h3>About the Role</h3><p>Join a data infrastructure team building a platform that turns information from multiple sources into reliable, up-to-date company intelligence. You will own the platform end-to-end, from architecture and ingestion through production operations, helping power downstream products with trusted data.</p><h3>What You'll Do</h3><ul><li><p>Design and build a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.</p></li><li><p>Develop intake pipelines for provider APIs, webhooks, files, and web scraping, with rate limiting and robust failure handling.</p></li><li><p>Orchestrate scheduled workflows and historical backfills using tools such as Airflow, Dagster, or Prefect.</p></li><li><p>Build event-driven systems with messaging or task queues, including retries, dead-letter queues, and controlled replay.</p></li><li><p>Preserve original payloads in Google Cloud Storage and transform data with dbt into raw, standardized, and curated layers.</p></li><li><p>Implement idempotent upserts, data contracts, automated validation, pipeline tests, and monitoring for freshness and failures.</p></li><li><p>Design and optimize PostgreSQL schemas and loading patterns, and integrate enrichment providers and LLM-based structured extraction.</p></li></ul><h3>What We're Looking For</h3><ul><li><p>At least 5 years building and operating production data platforms, with ownership spanning architecture, implementation, deployment, and ongoing operations.</p></li><li><p>Production experience with GCP and dbt, plus workflow orchestration such as Airflow, Dagster, Prefect, or Temporal, including dependency management, retries, and recovery.</p></li><li><p>Strong Python skills, including asynchronous HTTP and concurrent processing with tools such as asyncio, aiohttp, or HTTPX.</p></li><li><p>Strong SQL and PostgreSQL skills in data modeling, query optimization, and reliable incremental loading.</p></li><li><p>Experience with event-driven systems, queues, data contracts, raw and curated storage, retention policies, automated testing, and pipeline monitoring.</p></li><li><p>Experience in a startup or small engineering team is useful. Web scraping, entity resolution, company or people data enrichment, and LLM-based extraction are also relevant.</p></li></ul><h3>Compensation &amp; Benefits</h3><p>Annual base salary: $80,000 to $120,000 USD. Visa sponsorship is not available.</p><h3>Location</h3><p>Fully remote, candidates must be based in Latin America.</p>

Senior Data Engineer

<h3>About the Role</h3><p>Join a data infrastructure and analytics team building a platform that turns information from multiple sources into reliable, current company intelligence. You will own the platform across architecture, ingestion, and production operations, supporting products with trusted data.</p><h3>What You'll Do</h3><ul><li><p>Design a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.</p></li><li><p>Build ingestion from provider APIs, webhooks, files, and web scraping, with rate limits and robust failure handling.</p></li><li><p>Orchestrate scheduled workflows and historical backfills using Airflow, Dagster, Prefect, or similar tools.</p></li><li><p>Develop event-driven processing with messaging or task queues, including retries, dead-letter handling, and controlled replay.</p></li><li><p>Preserve source payloads in Google Cloud Storage and transform them with dbt into raw, standardized, and curated layers.</p></li><li><p>Implement idempotent upserts and safe retries to prevent duplicate records and data corruption.</p></li><li><p>Define data contracts, validation, pipeline tests, and monitoring for freshness and failures.</p></li><li><p>Optimize PostgreSQL schemas and loading patterns, and integrate enrichment and LLM-based structured extraction.</p></li></ul><h3>What We're Looking For</h3><ul><li><p>At least 5 years building and operating production data platforms that integrate multiple sources, with ownership from architecture through deployment and ongoing operations.</p></li><li><p>Production experience with workflow orchestration, including dependencies, retries, and recovery; Airflow is preferred.</p></li><li><p>Hands-on production experience with dbt and Google Cloud Platform.</p></li><li><p>Strong Python skills, including asynchronous HTTP and concurrent processing with tools such as asyncio, aiohttp, or HTTPX.</p></li><li><p>Strong SQL and PostgreSQL skills, including data modeling, query optimization, and incremental loading.</p></li><li><p>Experience with event-driven systems, messaging or task queues, data contracts, raw and curated storage, retention policies, automated testing, and pipeline monitoring.</p></li><li><p>Experience building platforms or substantial pipelines from scratch is valuable. Web scraping, entity resolution, BigQuery, Dataform, and LLM-based extraction are also relevant.</p></li></ul><h3>Compensation &amp; Benefits</h3><p>Base salary: $100,000 to $140,000 USD annually. Visa sponsorship is not available.</p><h3>Location</h3><p>Remote within Europe, including Norway, Switzerland, and the United Kingdom.</p>

<h3>About the Role</h3><p>Join an early-stage data infrastructure company building a platform that transforms information from multiple sources into reliable, current company intelligence. You will own the data platform end to end, from architecture and ingestion through production operations, helping ensure trusted data powers downstream products.</p><h3>What You'll Do</h3><ul><li><p>Design and build a multi-source platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.</p></li><li><p>Develop resilient intake from provider APIs, webhooks, files, and web scraping, including rate limits and failure handling.</p></li><li><p>Orchestrate scheduled workflows and historical backfills with tools such as Airflow, Dagster, or Prefect.</p></li><li><p>Build event-driven processing with messaging or task queues, including retries, dead-letter queues, and controlled replay.</p></li><li><p>Store original payloads in Google Cloud Storage and use dbt to transform data into raw, standardized, and curated layers.</p></li><li><p>Implement idempotent upserts, data contracts, automated validation, pipeline tests, and monitoring for freshness and failures.</p></li><li><p>Design and optimize PostgreSQL schemas and loading patterns for downstream use.</p></li><li><p>Integrate provider enrichment and LLM-based structured extraction into the platform.</p></li></ul><h3>What We're Looking For</h3><ul><li><p>At least 5 years building and operating production data platforms, with ownership from architecture through deployment and ongoing support; 8 or more years is a plus.</p></li><li><p>Production experience with workflow orchestration tools such as Airflow, Dagster, Prefect, or Temporal, including dependencies, retries, and recovery.</p></li><li><p>Hands-on production experience with dbt and Google Cloud Platform.</p></li><li><p>Strong Python skills, including asynchronous HTTP and concurrent processing with tools such as asyncio, aiohttp, or HTTPX.</p></li><li><p>Strong SQL and PostgreSQL experience in data modeling, query optimization, and incremental loading.</p></li><li><p>Experience building event-driven systems and implementing data contracts, retention policies, validation, testing, and monitoring.</p></li><li><p>Web scraping, entity resolution, data enrichment, and LLM-based extraction experience are helpful.</p></li><li><p>Comfort working with broad ownership and changing priorities in a small team; BigQuery and Dataform familiarity is a plus.</p></li></ul><h3>Compensation &amp; Benefits</h3><p>Base salary: $120,000 to $160,000 USD annually. Visa sponsorship is not available.</p><h3>Location</h3><p>Remote within the United States. New York-based candidates are welcome, but New York residence is not required.</p>

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Founding Engineer, Agents

Founding Engineer, Environments and Data

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

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