Member of Technical Staff, AI
Agencywithin · Long Island City, New York
About this role
## About the Role As a **Member of Technical Staff (AI)**, you’ll design applied AI systems and build the products around them across **frontend, backend, and data**. This role emphasizes **end-to-end product ownership**—you’ll define the problem, decide what to build, ship it, evaluate results, and maintain the system after launch. Most of your work will involve **LLM-powered applications**, **agent systems**, and the **evaluation and reliability** systems needed to run them in production. ## What You’ll Do (Full Lifecycle) - **Find product-market fit:** Start with a small version, test with users, and decide whether to continue, change direction, or stop. - **Improve what works:** Test changes and invest in versions that perform best. - **Expand and scale:** Grow adoption and make the system reliable under increased use. - **Maintain it:** Monitor performance, resolve problems, and keep improving post-launch. You’ll set direction with business partners—**they provide domain context and user needs**, and you decide how to scope, sequence, and develop the product. ## How We Work - **AI-native:** Use coding assistants and agent workflows throughout development; engineers are responsible for testing and reviewing outputs. - **Bias to ship:** Work directly with business teams, make product/technical decisions, and release in small increments. - **Fast feedback loops:** Use evidence (product data + feedback) to decide what to build next. ## What We’re Looking For - You’ve **owned products end to end**, from ambiguous problem definition through launch and ongoing operation. - You can decide **what to test first**, define success, and change course when results don’t support the plan. - AI tools are already part of how you **scope, build, test, and maintain** software. - You can choose between **model behavior**, **deterministic software**, and **human review** based on the problem. - You work independently, communicate tradeoffs, and keep stakeholders informed. ## Technical Foundation - Strong **Python** skills and experience building **production systems**. - Experience building production applications with **LLM APIs** (e.g., OpenAI, Anthropic, Vertex AI). - Experience building **agent workflows** (tools, external systems, state, multi-step tasks). - Experience designing **evaluations** for LLM systems (test cases, quality measures, regression testing, and review of production failures). - Understanding of **context management**, token limits, multi-turn conversations, tool calling, structured outputs, prompt design, and common failure modes. - Experience integrating **external APIs** and working with **SQL**. - Experience tracing/debugging behavior across model calls, application code, tools, and external systems. - Experience with **GCP, AWS, or Azure**. - Ability to build the product around AI components (frontend/backend/data). **TypeScript/React** and backend services are a plus. - Ability to explain technical tradeoffs and work directly with business teams. ## Strong Pluses - **Multi-agent architectures** - **Embeddings**, vector search, and **RAG** - Stateful or sandboxed code execution environments - Human review and approval workflows - Observability, model routing, latency management, and cost control - Document automation (Google Docs/Slides/PDFs) - Internal developer tools / productivity platforms - Data warehouses and transformation (BigQuery, Snowflake, Databricks, dbt, semantic layers like Cube/Looker/dbt Metrics) ##
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