Careers

We are looking for engineers and product builders who are AI-first and excited about commercial intelligence. If you are interested, send your profile, strongest work, or project links to zp@eigenlogic.cn.

Data Builder

For high-potential early to mid-early career data builders who can turn the outside world into data assets that agents can understand, cite, trace, and keep improving.

Why this role matters

  • You will work directly on the AI-first data foundation, organizing news, filings, companies, supply chains, reports, people, institutions, and events into usable data assets.
  • You will decide which facts should enter the system, how they should be modeled, captured, evaluated, and used by agents and report workflows.
  • This is a core seat on a small team. Strong data builders directly expand the cognitive boundary and trustworthiness of the agents.

What you will own

  • Build data maps that identify high-value sources, update cadence, collection priority, entity boundaries, event boundaries, and relationship boundaries.
  • Design schemas that work for storage, retrieval, citation, report generation, evaluation, and agent tool calling.
  • Design collection strategies across incremental crawling, deduplication, backfills, retry behavior, source credibility, quality checks, and evidence chains.
  • Move data from raw source into structured facts, citations, agent context, benchmarks, and product experiences.

Core capabilities

  • Strong ability in at least one of Python, SQL, or TypeScript, with the discipline to write solid scripts or data code.
  • Comfort with databases, schema design, ETL, crawling, APIs, queues, deduplication, incremental sync, testing, and data quality fundamentals.
  • Understanding of LLMs, RAG, tool calling, citation, evaluation, and agent context, with willingness to go deeper.

Signals we value

  • Experience with company data, industry-chain data, news, filings, financial data, knowledge graphs, search, or data products.
  • Experience with PostgreSQL, SQLAlchemy, Redis, vector search, data evaluation, data governance, or schema migration.

Product Builder

For high-potential early to mid-early career product builders who can define how people and agents work together, turning user goals, product structure, experience judgment, and engineering delivery into one clear path.

Why this role matters

  • You will work directly on the AI-first product path, shaping new experiences around conversation, reading, citation, reports, tasks, knowledge workflows, and multi-agent collaboration.
  • You will compress ambiguous product experiences into actionable issues, interaction state tables, acceptance criteria, and staging feedback.
  • This is a core seat on a small team. Strong product builders directly define product character, user trust, and team cadence.

What you will own

  • Use the core product path every day and identify friction, ambiguity, trust gaps, information noise, and missing next steps.
  • Turn real user tasks into understandable, trustworthy, and operable product paths across context, sources, tasks, state, results, and feedback.
  • Write actionable GitHub issues with scenarios, current experience, target experience, interface states, and acceptance criteria.
  • Join PR and staging review, turning experience feedback into review comments that engineering can act on directly.

Core capabilities

  • Ability to produce high-quality experience audits, flows, wireframes, prototypes, interaction state tables, and product acceptance criteria.
  • Understanding of complex information architecture, data-dense interfaces, task workflows, AI conversation, citation systems, and product trust mechanisms.
  • Fluency with Figma, FigJam, Markdown, GitHub issues, and similar communication and collaboration tools.

Signals we value

  • Experience with AI conversation products, agent products, knowledge workflows, investment research tools, data analysis platforms, or enterprise workbenches.
  • Experience with complex tables, card feeds, report readers, citation systems, multi-task workspaces, or visualization dashboards.

Agentic Builder Intern

An open-ended internship: enter the real work first, then use your work to define your track across data, product, engineering, systems, research, or design.

Why this role matters

  • You will enter a real AI-first product and engineering environment, contributing to real features, data, experience, and delivery.
  • You will work with Codex, Cursor, Claude, ChatGPT, automated review, CI, persona signals, and product feedback.
  • Strong interns can quickly own independent modules, issues, research, or product paths.

What you will own

  • Start from real tasks: experience audits, data-source research, schema sketches, scripts, page prototypes, test coverage, documentation, or issue definition.
  • Collaborate with agents on code reading, research, solution generation, sample construction, implementation verification, and retrospectives.
  • Deliver visible work every week: PRs, issues, designs, data samples, research notes, automation scripts, or experience reports.

Core capabilities

  • A strength in at least one area: Python, TypeScript, SQL, Figma, Markdown, data analysis, or research writing.
  • Familiarity with Git, command lines, AI tools, and basic collaboration workflows.
  • Course projects, personal projects, open-source contributions, design work, research reports, data projects, or automation tools.

Signals we value

  • Experience building AI applications, data crawlers, knowledge bases, product prototypes, automation tools, design systems, or research projects.
  • Publicly shareable work links, GitHub, portfolio, writing, project demos, or retrospective documents.