AI Engineer, AI Foundry — MAIA Platform

About the RoleMAIA is Prophet's next leap in AI — an always-available assistant that amplifies human insight. By integrating directly into our workflows, it turns AI into true Augmented Intelligence, extending our creativity, judgment, and expertise. Built on a multi-agent framework, MAIA connects specialized tools, data sources, and reasoning systems through one interface, so our people can do more, think deeper, and deliver sharper outcomes for clients.As an AI Engineer on the AI Foundry team, you'll be embedded in the group building and evolving MAIA, Prophet's multi-agent AI platform. This is a hands-on, technically intensive role. You'll own experiments end to end, build and test agents, benchmark model performance, and ship client-facing AI applications on the platform.A defining feature of this role is its position at the intersection of technical and non-technical worlds. Most of your day-to-day colleagues at Prophet come from consulting, strategy, and design backgrounds and have learned AI on the job; your deeper technical counterparts — engineers and platform developers — sit with our external technology partners. You'll operate with real autonomy, bridge those two audiences fluently, and often be the most technical person in the room.Your Day to DayExperimentation & Prototyping — Design and run experiments to validate new agent capabilities, including building agents, running scaled testing protocols, and benchmarking performance across use cases. Own experiments end to end and translate results into clear go/no-go recommendations.Agent Development & Testing — Draft agent specifications with defined data flows and system prompts. Drive prompt engineering, agent configuration, and iterative testing cycles to improve accuracy, reliability, and user experience.Technical Evaluation & Benchmarking — Assess technical approaches for platform capabilities (e.g., knowledge graph design, API integration patterns, retrieval-augmented generation strategies) and document tradeoffs across cost, speed, accuracy, and maintainability.Platform Development — Build and ship client-facing applications on MAIA, contributing to front-end and back-end implementation, writing and debugging production-quality code, and owning UX feedback and testing cycles.Performance Tracking & Analysis — Track product and system metrics (adoption, usage, latency, error rates) and synthesize findings into clear reports for the Foundry team and CoE leadership.AI Landscape Monitoring — Stay current with developments in LLMs, agent frameworks, and AI tooling, and surface relevant breakthroughs, tools, or techniques that could improve MAIA or the team's workflows.What You BringBachelor's degree in Computer Science, Machine Learning, Data Science, Engineering, or an equivalent technical background.~2–3 years of experience building AI/ML applications, data pipelines, or software systems.Strong Python and SQL, with fluent Git-based workflows and comfort in tools like VS Code, Vercel, and Supabase.Hands-on experience building LLM applications — RAG (chunking, embeddings, retrieval tuning) and agent frameworks such as LangChain, LangGraph, or LlamaIndex — plus solid prompt engineering.Practical ML experience with PyTorch, scikit-learn, or similar, and comfort with Pandas/NumPy for data work.Ability to ship a full-stack app end to end (e.g., Flask/FastAPI + React, deployed on Vercel/Supabase) and to design and consume REST APIs.A habit of evaluating and benchmarking your own work — measuring accuracy, cost, and latency, not just getting it running.Exposure to containerization and cloud (Docker, AWS/GCP/Azure) is a plus.Strong analytical thinking and a structured approach to breaking down ambiguous, scoped problems.Strong communication skills, especially translating technical concepts for consulting, strategy, and design colleaguesProphet has a hybrid working model that requires employees to be in the office 3+ days per week.Prophet is an equal opportunity employer. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. All employment, promotion, and evaluation decisions are based on qualifications, merit and business need.