Agentic AI Machine Learning Engineer

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 #J-18808-Ljbffr