Client Results Platform Engineer

EARNEST PartnersAtlanta, GA

About The Position

We are seeking a Client Results Platform Engineer to build the systems and intelligence that ensure clients can trust everything they see from the firm. This is a role for someone who wants to own a function that sits at the heart of the client relationship and reimagine how it operates, combining deep ownership with hands-on work applying data, AI, and modern tooling. The ideal candidate is energized by getting things right at scale and sees how the data and workflows behind a function can be rebuilt, not just maintained. You will gain broad exposure across operations, trading, compliance, and product, and work on the core systems the firm runs on, with the mandate to make them better.

Requirements

  • Experience in investment operations, fund accounting, performance, client reporting, or a related investment management environment.
  • Familiarity with the performance lifecycle and interest in how reporting, operations, and investment workflows evolve through technology and process design.
  • Curiosity about how reporting, operations, and investment workflows can be reimagined through data, automation, and AI, and the drive to go deep on it.
  • Strong analytical and problem-solving skills, with the ability to evaluate tradeoffs and thrive in a fast-moving environment where priorities continue to evolve.
  • Strong communication skills, ownership mentality, and willingness to challenge existing assumptions constructively.

Nice To Haves

  • Experience with workflow tools, automation, analytics, or process improvement is helpful, but curiosity, adaptability, and a learning orientation matter more than any single technical skillset.

Responsibilities

  • Own the accuracy and integrity of the firm’s client data, performance, and reporting across reconciliations, cash flows, NAVs, and corporate actions.
  • Design and evolve the next-generation client data and reporting platform: its workflows, automation, data architecture, and operating model.
  • Build the intelligence and controls that let the function anticipate problems rather than react to them.
  • Develop AI-enabled tools and decision-support systems that change what the function is capable of.
  • Partner with investment, trading, compliance, operations, and technology teams toward an integrated front-to-back environment.
  • Rethink how a modern investment organization should operate in an AI-enabled environment.
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