SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Lemrock builds infrastructure for agentic commerce, enabling brands to sell directly within conversational AI interfaces like ChatGPT and Perplexity. The company has raised €7M in seed funding, serves 150+ brand clients, and processes 100M+ conversations monthly.
You will join a tight-knit team with high product standards and direct access to production deployment. Your role focuses on building and scaling the agentic infrastructure powering Lemrock's commerce intelligence system.
Key responsibilities:
- Analyze large-scale conversational interaction datasets (100M+ events/month) to uncover behavioral patterns, intent signals, and performance drivers
- Design and deploy agentic pipelines end-to-end, from data ingestion and enrichment to model orchestration, monitoring, and continuous improvement, integrated into systems exposed to millions of requests daily
- Build autonomous agents that maintain accuracy and currency in the knowledge infrastructure
- Translate insights into production iteration loops by updating, fine-tuning, and improving recommendation and ranking algorithms with tight constraints on latency, robustness, and business outcomes
- Design and train new recommendation models from scratch when needed, with focus on scalability, evaluation rigor, and real-world deployability
The team includes two repeat YC founders, a former strategy/innovation director with 10 years in the sector, and ex-strategy consultants from McKinsey QuantumBlack and BCG. You'll own mission-critical topics, grow rapidly, and shape the company's trajectory in the emerging agentic interfaces space.
REQUIREMENTS:
- Strong academic background (MVA, ENS, X, Central, or equivalent)
- 2+ years of experience in AI, Agentic Systems, ML/Deep Learning, statistics, or NLP
- Experience prototyping and deploying AI models into production
- Experience with production systems (APIs, monitoring, optimization)
- Strong interest in LLMs, recommendation systems, and conversational systems; experience building agentic pipelines, agent orchestration, fine-tuning
- Comfortable with AI coding tools (Claude Code, Cursor)
- Thrives in ambiguity and 0-to-1 environments
- Fluent in English; French is a plus
Tech stack (required): Agentic frameworks (e.g., Langchain) and/or native SDKs like OpenAI/Anthropic; observability and evaluation for LLM/agent workflows; vector search, scoring, prompting, LLM orchestration; hybrid recommender systems, causal inference, probabilistic models.
Bonus skills (appreciated but not required): TypeScript; Docker, GCP, PostgreSQL, Redis, Vector DBs, PostHog; CI/CD.
