AI Engineer

Contract: Claude AI Engineer (3 Months)

Location: Remote (North America preferred)

Duration: 3-month contract (with potential extension)

Start: ASAP

About the Role

We’re looking for a highly technical Claude AI Engineer to help us design, build, and refine an AI-powered sales intelligence CRM. This system will leverage cutting-edge LLM capabilities to automate research, enrich data, and generate high-quality sales insights at scale.

You’ll work closely with product, growth, and engineering to rapidly prototype and productionize AI workflows that directly impact revenue teams.

What You’ll Do

* Architect and implement LLM-powered workflows using Claude (and complementary models where needed)

* Build intelligent agents for:

* Lead enrichment and qualification

* Account research and summarization

* Personalized outbound generation

* Design prompt systems, memory structures, and retrieval pipelines (RAG)

* Integrate structured and unstructured data sources into a unified intelligence layer

* Optimize outputs for accuracy, consistency, and latency

* Rapidly iterate on prototypes and ship production-ready features

* Collaborate cross-functionally to align AI outputs with real sales workflows

What We’re Looking For

* Deep experience working with LLMs in production environments

* Strong hands-on experience with Claude / Anthropic APIs (or similar frontier models)

* Expertise in:

* Prompt engineering and evaluation

* RAG pipelines and vector databases (e.g., Pinecone, Weaviate, FAISS)

* Agent frameworks and orchestration

* Proficiency in Python (Node.js is a plus)

* Experience building internal tools, automation systems, or CRM enhancements

* Strong product intuition — you understand what makes outputs actually useful to sales teams

* Ability to move fast, iterate, and operate with minimal oversight

Bonus Points

* Experience with sales tech, CRMs, or GTM tooling

* Background in growth, marketing ops, or sales ops

* Familiarity with data pipelines and enrichment providers (Clearbit, Apollo, etc.)

* Experience optimizing LLM cost/performance tradeoffs at scale