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Protocol Intelligence
Data-driven signals on your job's competitivenessMetro-based mid-level ML role with common title and broad required skills, causing moderate applicant competition.
Requires specialized agentic/LLM and production ML experience, reducing transferability from non-AI backgrounds.
Explicit 6+ years, 2+ years LLM experience, and demonstrable agentic project artifacts create strict screening.
Job Description
Structured overview of role & requirementsAbout This Role
Lead design and delivery of connected agentic AI systems combining LLMs, tools, APIs, data, and human controls to improve decision-making and automate business processes.
Own architecture of multi-agent workflows covering orchestration, task routing, error recovery, and escalation, ensuring deployment and adoption of production-ready machine learning solutions.
Translate business needs into technical requirements, build evaluation frameworks, provide technical mentorship, and maintain production code quality and documentation.
Minimum Requirements
Bachelor’s or master’s degree in Computer Science, AI, ML, Data Science, Engineering, or related quantitative field.
Minimum 6 years professional experience in data science, ML, applied AI or software engineering; at least 2 years building and delivering LLM, generative, or agentic AI solutions.
Strong expertise in Python programming, agentic AI engineering, RAG and knowledge systems, SQL, software delivery tools (Git, CI/CD), and evaluation/safety frameworks.
Demonstrable hands-on experience building connected agentic systems beyond simple chatbots; able to provide specific examples and technical details.
Ideal Candidate Profile
Experienced technical leader comfortable balancing AI research/experimentation with production-grade engineering and stakeholder communication.
Skilled in multi-agent AI system design and orchestration with proven ability to deliver measurable business impacts via automation.
Used to working in advanced AI environments involving retrieval-augmented generation, human-in-the-loop controls, and continuous evaluation and improvement frameworks.