The leader in AI-native data preparation and analysis, Prophecy is revolutionizing how theworld’s top enterprises turn data chaos into reliable insights. We introduce the AI-native datalifecycle (generate, refine, deploy) where our industry leading AI agents and humans work hand-in-hand in visual and document interfaces to analyze, transform and prepare data, to shiptrusted insights at enterprise scale.
Must-Have Skills:
- Hands-on LLM/agent building (e.g., LangChain/Graph, CrewAI) and tuning to qualitybenchmarks.
- Experience with semantic search, RAG, and vector databases.
- Experience with prompt engineering and optimization.
- Agentic Use Cases: Hands-on experience building and deploying agents in at least oneof the following scenarios:
- Workflow Orchestration: Automating multi-step processes (e.g., ETL pipelines,supply chain optimization, or CRM workflows like Salesforce Agentforce).
- Code Generation/Assistance: Developing or debugging code autonomously(e.g., similar to Devin AI or GitHub Copilot extensions).
- Data Analysis/Transformation: Querying, manipulating, or analyzing dataacross sources (e.g., topic extraction, document analytics in vector DBs likeWeaviate).
- Personalized Assistance: Tailoring recommendations or plans (e.g., e-commerce, education, or finance agents).
- Autonomous Decision-Making: Real-time decisions in domains like trading orhealthcare (e.g., crypto trading, medical workflow optimization).
- Content Creation: Generating text, art, or media (e.g., social mediaautomation, presentation creation).
- Multi-Agent Systems: Collaborative agents for simulations or transactions(e.g., policy-constrained evaluation, machine-to-machine commerce).
- Versatile software developer: fluency in Python, REST APIs, microservices in publiccloud; some experience with Go, AWS, k8s, java, Scala.
- Builder mentality: Demonstrated experience taking ideas to production.
£4,000 signing bonus paid to you on hire.
Requirements
- Hands-on LLM/agent building (e.g., LangChain/Graph, CrewAI) and tuning to quality
- Experience with semantic search, RAG, and vector databases.
- Experience with prompt engineering and optimization
- Agentic Use Cases: Hands-on experience building and deploying agents in at least one
- Versatile software developer: fluency in Python, REST APIs, microservices in public
- Builder mentality: Demonstrated experience taking ideas to production.
Tech stack
- Java
- Machine Learning
- Scala
- Artificial Intelligence