Distribution & Analytics GenAI Forward Deployed Engineer

ameriprise; Boston (MA); Hybrid; USD 145,000 - 175,000; Full time

Job summary

Ameriprise Financial is seeking a frontend role embedding with Sales, Marketing and Distribution teams across North America and EMEA to build AI prototypes that translate into live tools. You will prototype and productionise solutions using CRM data and accelerate adoption by testing with users.

The ideal candidate will have strong Python skills, AWS depth, and hands-on experience with Bedrock AgentCore, CI/CD, and secure data practices. This is a hybrid role with rapid iteration expectations.

Qualifications

• Direct experience working with Sales, Marketing or Distribution teams in asset management or financial services.
• Strong Python skills and AWS engineering depth for production‑quality code.
• Experience deploying agentic AI and modern software practices (CI/CD, version control, API design).

Responsibilities

• Turn ambiguous commercial needs into high‑value problems with Sales, Marketing and Distribution teams.
• Rapidly prototype and iterate LLM‑enabled tools tied to real CRM and data.
• Take prototypes from whiteboard to working solutions with minimal handoffs.
• Integrate with LLM enablement infrastructure and ensure security, governance and auditability.
• Validate with users and scale prototypes with engineering.

Skills

Python

AWS

CI/CD

API design

Tools

Amazon Bedrock AgentCore

CI/CD tooling

Job description

About Our Company

We're a diversified financial services leader with more than $1.5 trillion in assets under management, administration and advisement as of year-end 2024. Our team of 22,000 people across 19 countries, serves more than 3.5 million individual, small business and institutional clients. We are a longstanding leader in financial planning and advice, a global asset manager and an insurer. Our unwavering focus on our clients and strong financial foundation connects each of our unique businesses - Ameriprise Financial, Columbia Threadneedle Investments and RiverSource Insurance and Annuities. Here, we foster meaningful careers, invest in the future, and make a difference for clients, institutions and communities around the world.

Job Description

This role sits at the front line between product teams and the global Sales & Marketing teams. Role will embed with real users, build working AI prototypes in days, prove what earns adoption, and partner with engineering to productionise the viable ideas.

About the Role

Columbia Threadneedle is at an inflection point in how it uses AI across its commercial engine. We have the infrastructure, the CRM and commercial data, and world-class Sales, Marketing and Distribution teams - what we're building now is the connective tissue between them: people who can sit with a distribution team, understand the problem they're trying to solve, and build something that works by the end of the week.

This is not a support role. It is not a roadmap role. You will be embedded directly with Sales, Marketing and Distribution teams across North America and EMEA, working on problems that shape how we win and retain clients - and you'll help drive your solutions from the first conversation to the moment they go live. You show what should ship by testing with users, not by writing decks. The best candidates we've spoken to light up when they hear that. If that's you, read on.

What You'll Do

• Partner directly with Sales, Marketing and Distribution users to turn ambiguous commercial needs into sharply scoped, high-value problems.
• Rapidly prototype and iterate on LLM-enabled tools - spanning CRM intelligence, meeting preparation, campaign and audience analytics, and distribution reporting - grounded in real CRM and commercial data.
• Take prototypes from whiteboard to working solution, working largely independently without a detailed specification handed to you.
• Integrate solutions with LLM enablement infrastructure (agent runtimes & internal data platforms, CRM and marketing analytics platforms) and ensure outputs meet the security, governance and auditability standards of a regulated environment.
• Validate with users through short feedback loops, stopping or redirecting ideas that don't earn adoption; identify prototypes with production potential and partner with engineering to scale them.

What Success Looks Like

In your first year, you'll have shipped tools that Sales, Marketing and Distribution teams actually use - not prototypes that live in a demo environment, but working solutions embedded in how commercial decisions get made at CTI.

The feedback loop here is immediate. You're not writing tickets for a product team or waiting six months for a release cycle. You sit with the people who have the problem, you build the solution, and you see it land - or you iterate until it does.

By the end of year one, the measure of success is simple: business teams come to you when they have a problem they think AI can solve. And you're right often about whether it can - and how.

What We're Looking For

Commercial & Distribution Domain

Direct experience working alongside Sales, Marketing or Distribution teams in asset management or financial services - commercial technologists, distribution analytics, or sales/marketing enablement backgrounds are strongly preferred.

Enough fluency in how funds are sold, serviced and reported (CRM, campaigns, mandates, flows) to contribute to commercial discussions, not just take requirements from them.

Engineering

Strong Python skills to drive production-quality code, with genuine AWS engineering depth and a bias for rapid prototyping over perfect specifications.

Hands‑on experience building or deploying agentic AI on Amazon Bedrock AgentCore (the ability to become productive in AgentCore quickly is essential), plus modern software practices - CI/CD, version control and API design.

The Hybrid

A track record of independently taking ambiguous problems from concept to working solution in fast-moving, loosely defined environments.

The communication skills to operate fluently on the distribution floor and in the engineering team - in the same day - applying security, data-governance and responsible‑AI guardrails with appropriate evaluations and human oversight.

Base Pay Salary

The estimated base salary for this role is $145,000 - $175,000 / year. We have a pay-for-performance compensation philosophy. Your initial total compensation may vary based on job-re