AI Engineer

Digital Waffle; New York (NY); Sur place; USD 140 000 - 200 000; Plein temps

Avantages offerts par ce poste

In-office in New York

Competitive compensation

Résumé du poste

Digital Waffle in New York is seeking an AI Engineer to design, build and ship LLM-powered product features and agentic workflows into production. This is a hands-on, build-focused role working alongside product and users, not a pure research position.

You will work with Python and TypeScript, handle tool calling, RAG, vector search and eval pipelines, integrate with React/Next.js surfaces, and own AI layer metrics like cost, latency and reliability while collaborating closely with model

Qualifications

• Production experience shipping LLM-powered features.
• Strong Python and TypeScript in production.
• Familiarity with tool calling, RAG and vector databases.

Responsabilités

• Design and ship production LLM features and agents.
• Build the applied AI toolkit end to end (tool calling, RAG, vector search).
• Work with model APIs (Anthropic, OpenAI, Google) and open-source models as suitable.
• Build evaluation pipelines to measure quality.
• Integrate agents into React/Next.js product surfaces.
• Own AI layer cost, latency and reliability.

Connaissances

Python

TypeScript

LLM features

Production experience

API integration

Outils

Anthropic API

OpenAI API

LangSmith

Vector databases

Description du poste

A high-growth AI-native startup is hiring an AI Engineer in New York to design, build and ship LLM-powered product features and agentic workflows into production.

This is a build role focused on the applied AI stack: prompts, retrieval, tools, agents, evals and the glue that connects them to a real product. You’ll work close to product and real users, not inside a research lab.

Location: New York, 5 days per week in office

What you’ll be doing:

• Design and ship production LLM features and agents using Python and TypeScript
• Build the applied AI toolkit end to end: tool and function calling, RAG, vector search, structured output, prompt management, context handling
• Work directly with foundation model APIs (Anthropic, OpenAI, Google) and open-source models where it makes sense
• Build evaluation pipelines (Braintrust, LangSmith or custom) so quality is measurable rather than anecdotal
• Integrate agents into existing product surfaces built in React and Next.js
• Own cost, latency and reliability of the AI layer as first-class concerns
• Use AI tooling (Claude, Cursor and similar) across your workflow to compress the build cycle

What you’ll need:

• Strong Python and TypeScript, with real production experience shipping LLM-powered features
• Practical grasp of the applied AI stack: function calling, RAG, vector databases, structured output, prompt engineering, context management
• Comfort with at least one agent framework or SDK, with a view on why the abstractions exist
• Experience building evals and guardrails for LLM output
• Solid API, integration and backend engineering fundamentals
• Fluent in modern AI engineering tools and able to use them to raise output
• Happy working 5 days a week in-person with a small, high-intensity team

Nice to have:

• Prior work on agentic systems in production (not just prototypes)
• Experience with multimodal models (vision, audio, video)
• Exposure to fine-tuning or post-training of foundation models

This role would suit an AI engineer who wants to ship real LLM product into users’ hands, not write another whitepaper.