Agentic-Workflow MLE
Prophecy · San Francisco, CA
- On site
- Full-time
- $350,000 / year
- San Francisco, CA
Job highlights
- Build AI-native data preparation and analysis solutions.
- Develop and deploy advanced AI agents using LLMs.
- Work with semantic search, RAG, and vector databases.
- Leverage Python, REST APIs, and cloud microservices.
- Contribute to a groundbreaking data revolution platform.
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, Code Generation/Assistance, Data Analysis/Transformation, Personalized Assistance, Autonomous Decision-Making, Content Creation, Multi-Agent Systems.
- 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
Mid to Staff Level
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
Compensation
$250,000–$350,000
Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to achievements, skills, experience, or work location. The range listed is just one component of the compensation package offered to candidates.
Benefits and Perks
- Prophecy covers 99% of employee health insurance premiums and 75% for dependents
- We offer $200 per month towards remote work, wellness, gyms, massages, facials, and more!
- Flexible PTO
- Professional development allowance
- Company sponsored Long Term Disability and Life Insurance, FSA/HSA, dental, vision, and more
- Ability to have your fingerprint on an innovative platform
- End-to-end ownership of your projects.
- Benefits and perks may vary per country
Equal Opportunity Employer
Prophecy is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, national origin, age, disability, or veteran status.
Key skills/competency
- Machine Learning Engineering
- LLM Building
- Agentic Use Cases
- Python Development
- REST APIs
- Microservices
- Knowledge Graphs
- Vector Databases
- Prompt Engineering
- Software Engineering
Skills & topics
- Machine Learning Engineer
- LLM
- AI Agents
- LangChain
- CrewAI
- RAG
- Vector Databases
- Prompt Engineering
- Python
- Software Engineering
- Data Analysis
- Workflow Orchestration
- Code Generation
- Hybrid Role
- Mid-Level
- Staff Level
How to get hired
- Tailor your resume: Highlight your LLM/agent building, prompt engineering, and Python development skills.
- Showcase production experience: Detail projects where you took ideas from concept to deployment.
- Quantify achievements: Use data to demonstrate the impact of your AI/ML contributions.
- Prepare for technical interviews: Brush up on LLMs, RAG, vector databases, and software architecture.
- Research Prophecy: Understand their AI-native approach and data revolution mission.
Technical preparation
Build and tune LLMs with LangChain or CrewAI.,Implement semantic search, RAG, and vector databases.,Develop Python microservices and REST APIs.,Practice prompt engineering and agentic workflows.
Behavioral questions
Describe a complex AI agent you built.,How do you handle ambiguity in requirements?,Tell me about a time you took an idea to production.,How do you collaborate with cross-functional teams?
Frequently asked questions
- What are the primary responsibilities for a Machine Learning Engineer at Prophecy?
- As a Machine Learning Engineer at Prophecy, you will focus on building and deploying AI-native data preparation and analysis solutions. This includes hands-on LLM/agent building, working with semantic search and RAG, optimizing prompts, and developing software using Python and cloud microservices.
- What specific agentic use cases are relevant for this Machine Learning Engineer role at Prophecy?
- Prophecy seeks experience in agentic use cases such as workflow orchestration, code generation/assistance, data analysis/transformation, personalized assistance, autonomous decision-making, content creation, and multi-agent systems. Demonstrating experience in at least one of these areas is crucial.
- What technical skills are considered 'must-haves' for this Machine Learning Engineer position at Prophecy?
- The must-have skills include hands-on LLM/agent building (e.g., LangChain, CrewAI), experience with semantic search, RAG, vector databases, and prompt engineering. Proficiency in Python, REST APIs, and cloud microservices is also essential.
- What makes a candidate stand out for the Machine Learning Engineer role at Prophecy?
- Candidates who stand out will have expertise in knowledge graphs, experience integrating them with AI systems, ML/LLM work in code generation or text-to-SQL, experience with big-data engines like Spark, compiler development, or optimizing ML models for production.
- What is the work arrangement and location for this Machine Learning Engineer job at Prophecy?
- This is a hybrid role requiring 2-3 days a week in the office. The specific location is not explicitly stated in the job description, but the hybrid nature implies a company office presence is required.
- What is the expected experience level for the Machine Learning Engineer position at Prophecy?
- Prophecy is looking for a Mid to Staff Level candidate with a minimum of 6+ years of Software Engineering experience, including at least 2 years in AI/ML.
- What is the compensation range for the Machine Learning Engineer role at Prophecy?
- The base pay range offered for this position is $250,000 to $350,000 annually. This is just one part of a comprehensive compensation package.
- Does Prophecy offer remote work options for this Machine Learning Engineer role?
- While the role is described as hybrid, Prophecy does offer $200 per month towards remote work, wellness, gyms, massages, and more, indicating some flexibility and support for remote-related expenses.