Anthropic
Develops reliable, interpretable AI systems
Research Engineer - Economic Research Data Platform
+ Optional equity donation matching
At least 25% of work time must be in an office.
About the job
- Significant experience building data-intensive applications, pipelines, or internal tooling in production.
- Experience with cloud infrastructure platforms such as AWS or Google Cloud Platform.
- Ability to write clean, well-documented Python code.
- Intuition for analytics workflows and empathy for researchers and data scientists.
- Ability to make technical decisions with incomplete information while maintaining high engineering standards.
- A full-stack mindset and willingness to solve problems end-to-end.
- Strong communication skills for collaborating with economists, researchers, and cross-functional partners with varying levels of technical expertise.
- Interest in the societal impacts of the work and AI's economic implications.
- A bachelor's degree or an equivalent combination of education, training, and experience.
- A field relevant to the role, demonstrated through coursework, training, or professional experience.
- Build and operate data pipelines that transform raw usage data into clean, reusable, privacy-preserving datasets.
- Design new systems, including developing classifiers, training probes on model internals, and building the ML pipelines behind them, to understand Claude usage and its economic impact.
- Build self-service workflows to ingest and integrate external data sources so they are interoperable with internal datasets.
- Develop the APIs, libraries, and interfaces that serve data to researchers and the public.
- Partner with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic's safety mission.
- Contribute to the team roadmap, documentation, and practices that enable self-service data access while maintaining safety and governance standards.
- Ensure data reliability, integrity, and privacy compliance across economic research data infrastructure.
- Experience with modern data transformation, orchestration, and query frameworks.
- Experience building systems and products on top of large language models.
- Experience with privacy-preserving data systems or data governance and lineage tooling.
- Experience building and operating web services and the infrastructure underneath them.
- Experience with full-stack development or complex data visualization.
- Background in econometrics, statistics, or quantitative social science.
- Experience working in environments where engineers partner closely with quantitative users, such as research labs, trading firms, or analytics companies.
About the company
Anthropic focuses on AI research to build reliable, interpretable, and steerable AI systems. Its main product, Claude, is an AI assistant designed to handle tasks at any scale for clients across industries, delivered through deployment and licensing along with specialized AI R&D services. Claude works by combining natural language processing, human feedback, reinforcement learning, and interpretability techniques to produce a capable, controllable AI assistant that can assist with a wide range of tasks. The company differentiates itself from competitors by prioritizing safety, transparency, and controllability—emphasizing reliability, interpretability of model behavior, and user-controlled steerability in its AI systems. Anthropic’s goal is to make AI systems that people can trust and efficiently use to improve operations and decision-making across sectors.
Company Size
5,001-10,000
Company Stage
Debt Financing
Total Funding
$182.8B
Headquarters
San Francisco, California
Founded
2021
Get referred to Anthropic
See people who can refer or advise you
Simplify's Take
What believers are saying
- Claude Code crossed $1 billion ARR in 2026, proving developer demand.
- SpaceX's 300-megawatt deal adds immediate capacity for Claude growth.
- Anthropic's $965 billion valuation and $65 billion raise fund aggressive scaling.
What critics are saying
- The $1.5 billion copyright settlement exposes training-data liability across future lawsuits.
- Google's $40 billion investment and Amazon's $20 billion expansion increase customer concentration.
- Safety rhetoric collides with biolab scrutiny, creating reputational and regulatory backlash risk.
What makes Anthropic unique
- Claude Code Projects coordinates parallel sessions with persistent project memory.
- Anthropic pairs frontier-model research with safety, interpretability, and product shipping.
- Amazon, Google, and SpaceX partnerships secure compute and distribution advantages.
Help us improve and share your feedback! Did you find this helpful?
Benefits
Flexible Work Hours
Paid Vacation
Parental Leave
Hybrid Work Options
Company Equity
Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↑ 3%2 year growth
↑ 2%Anthropic has confirmed it operates a wet biology lab where its AI models conduct physical experiments. The company's head of life sciences, Eric Kauderer-Abrams, told Reuters the lab functions like most biotech facilities, conducting some in-house research whilst collaborating with external partners. The lab emerged from Anthropic's April acquisition of Coefficient Bio, a stealth AI biotech startup. Anthropic declined to specify the lab's focus, except to say it isn't working on drug discovery, likely to avoid competing with pharmaceutical customers and partners like Novo Nordisk. The lab's existence has drawn scrutiny given recent warnings from Anthropic researchers about AI's existential risks. CEO Dario Amodei recently called for industry self-regulation, repeatedly citing bioterrorism as one of AI's biggest threats.
AI research and products that put safety at the frontier.
Brad Gerstner, founder of Altimeter Capital, says leading AI labs must increase their combined annual revenue from roughly $100 billion to at least $180 billion by year-end to sustain the AI trade. Speaking at the All-In Summit, he called AI lab revenue "the single most important data point in the market today." Gerstner estimates that Anthropic, OpenAI, and xAI had a combined run rate of approximately $100 billion in July. The revenue growth is needed to support massive infrastructure spending by Microsoft and Alphabet, who are building computing capacity that AI labs rent. Altimeter held 9.41 million Nvidia shares worth $1.88 billion at 30 June, representing about 19% of its US equity portfolio. The firm also holds stakes in Anthropic and OpenAI.
Anthropic has revamped projects in Claude Code, allowing users to run multiple parallel sessions for a single project. The feature, currently in beta for select Pro and Max subscribers, enables Claude to manage several related tasks simultaneously by creating separate cloud session threads, each working on its own git branch. Projects can coordinate tasks like authorization, databases, and caching concurrently. A coordinator directs the threads, surfacing overlaps as merge conflicts when necessary. Claude Code now offers five ways to run multiple tasks simultaneously, including subagents, Agent View, Agent Teams, Dynamic Workflows, and projects. Anthropic warns that projects consume tokens quickly since each thread represents a full Claude Code session. Team and Enterprise plans don't yet have access. Anthropic reportedly posted $11.5 billion in Q2 revenue, with adjusted operating profit excluding stock-based compensation.
OpenAI launched Astra for Law on Thursday, its artificial intelligence offering tailored for legal work. The product includes plugin tools, enhanced legal case search capabilities, and custom model adjustments for building applications. The launch targets the legal technology industry and America's 200 largest law firms. It follows OpenAI's recent ChatGPT for Financial Services release and mirrors a similar legal product Anthropic introduced in May. Astra for Law runs on OpenAI's most advanced model, customised to reduce hallucinations and improve legal reasoning by grounding responses in case law. The tool generates responses twice as long as standard Astra outputs. Legal technology companies including Harvey, Legora, and Thomson Reuters can integrate the tool into their products through available plugins. OpenAI plans to add a citations feature developed for its financial services product.