About the role
About Prophecy The leader in AI-native data preparation and analysis, Prophecy is revolutionizing how the world’s top enterprises turn data chaos into reliable insights. We introduce the AI-native data lifecycle (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 ship trusted insights at enterprise scale. Don’t miss the rocket ship—join Prophecy and build the next data revolution. Must-Have Skills : Hands-on LLM/agent building (e.g., LangChain/Graph, CrewAI) and tuning to quality benchmarks. 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 of 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 data across sources (e.g., topic extraction, document analytics in vector DBs like Weaviate). Personalized Assistance : Tailoring recommendations or plans (e.g., e-commerce, education, or finance agents). Autonomous Decision-Making : Real-time decisions in domains like trading or healthcare (e.g., crypto trading, medical workflow optimization). Content Creation : Generating text, art, or media (e.g., social media automation, 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 public cloud; some experience with Go, AWS, k8s, java, Scala. Builder mentality: Demonstrated experience taking ideas to production. What Will Make You Stand Out Expertise in building and managing Knowledge Graphs, including entity extraction, linkage, and ontology design. Experience integrating Knowledge Graph with AI systems for retrieval, reasoning, and agent context (e.g., enriching with LLM). ML/LLM work in code generation (e.g., Codex, text-to-SQL), semantic extraction, or knowledge graphs (e.g., Neo4j, Neptune). Experience with big-data engines like Spark. Compiler development for languages like SQL, Python, or Scala. Optimization of ML models for low-latency, high-throughput production use. Contributions to open-source AI/ML projects (e.g., Hugging Face, PyTorch). Expertise in retrieval systems or vector databases (e.g., Pinecone, Weaviate). Skill in evaluating tech and driving build/buy decisions Seniority : Staff or Principal Location: This is a Hybrid role with 2-3 days a week in office. However, this can vary week to week. Experience : 6+ years of Software Engineering experience minimum with 2+ of these being in AI/ML