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
Key Responsibilities
- Serve as a trusted advisor to investment leaders, translating investment strategies, research priorities, and business challenges into innovative AI-enabled solutions that improve investment outcomes and organizational efficiency.
- Drive the design and delivery of proof-of-concept and production-ready AI capabilities, leveraging advanced analytics, machine learning, and LLM technologies to accelerate investment insights and decision-making.
- Partner across Investments, Technology, Data, Risk, and Compliance functions to ensure solutions meet enterprise standards for security, governance, scalability, and regulatory compliance.
- Influence the AI and investment technology roadmap by identifying high-value opportunities, evaluating emerging capabilities, and promoting adoption of innovative solutions across the investment organization.
- Lead the transition of successful prototypes into sustainable enterprise capabilities, partnering with engineering and platform teams to scale solutions and realize long-term business value.
Required Qualifications
- 10+ years of combined experience across investment management, quantitative research/strategy, and hands-on software or AI engineering, with demonstrated success taking investment problems from concept to working solution.
- Direct experience working alongside trading desks, portfolio managers, or investment researchers, with desk strategist, quant strat, or research technologist backgrounds strongly preferred.
- Hands-on experience building and shipping LLM enabled/integrated applications: RAG/embeddings, agentic workflows, prompt engineering, API integration.
- Strong Python development skills producing production-quality code.
- Expertise with cloud infrastructure and modern software practices (CI/CD, version control, API design).
- Fluency in at least one asset class (equities, fixed income, multi-asset, or macro) at a level where you can challenge and contribute to investment discussions, not just support them.