What's the Role About?
As an Agent Engineer at CommerceClarity, you'll build and ship the AI agents that run product data infrastructure for enterprise retailers across Europe. These aren't prototypes — they're production systems handling thousands of catalog operations per day, where reliability, cost, and accuracy directly impact our customers' revenue.
You'll own agents end-to-end: prompt design, orchestration, evaluation, deployment, monitoring, and continuous iteration. You'll work alongside engineers, the CPO, and customer‐facing teams to ship agents that hold up in messy real‐world conditions — and push the boundaries of what AI can do in commerce operations.
Key Responsibilities
- Design, build, and ship production‐grade AI agents across catalog enrichment, classification, assortment, and publishing
- Own the full agent lifecycle: from first prompt to deployed system, with continuous evaluation and iteration
- Build orchestration systems, RAG pipelines, and evaluation frameworks that keep agents reliable at scale
- Integrate Anthropic, OpenAI, and other foundation models — making strategic calls on model selection, cost, and latency
- Optimize token usage, caching, and observability across the agent stack
- Translate messy customer problems into agents that solve them — working closely with the Agent PM and Solution Engineering teams
- Surface patterns from production back to product and engineering, shaping the agent platform roadmap
- Raise the technical bar for how AI agents are built, tested, and operated at CommerceClarity
Who You Are
Essential
- 3+ years of engineering experience shipping production systems, with hands‐on LLM work in the last 12+ months
- Production experience integrating LLM APIs (Anthropic, OpenAI, or similar) into real products
- Strong prompt engineering chops with systematic evaluation approaches — you don't ship by vibes
- Comfortable building and operating RAG pipelines, agent orchestration, and vector search (Pinecone, Weaviate, or similar)
- Solid Python skills, fluent in modern AI tooling and libraries
- Deep understanding of LLM tradeoffs: cost, latency, quality, failure modes
- Comfortable with ambiguity, fast iteration, and incomplete information
- Clear thinker, low ego, high standards, open to feedback
- Fluent in English with strong written communication
- Genuine curiosity about where AI is going next
Nice to have
- Experience building or leading an AI agent product in production
- Familiarity with eval frameworks, LLM observability, and ML monitoring
- Background in B2B SaaS or an AI‐native company
- Experience with traditional ML/NLP techniques and frameworks (transformers, scikit‐learn)
- Knowledge of LangChain, LlamaIndex, or similar orchestration frameworks
- E‐commerce, retail, or catalog data background
- Open source contributions or technical writing on AI/agents
What We Offer
- Meaningful early‐stage equity
- Competitive salary
- Direct impact on the agent platform powering enterprise retailers across Europe
- Tight feedback loops with founders, customers, and the engineering core
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