AI Consulting Associate Program, DriveWealth

• Must have a graduation date in 2026 or 2027
• Pursuing a degree in Computer Science, Machine Learning, Mathematics, Engineering, or related technical field. Must have a graduation date in 2026 or 2027
• Experience programming in Python (for automation, prototyping, and scripting) and SQL
• Familiarity with APIs, JSON, and basic service integration
• Foundational understanding of large language models and how they are used in applications (prompting, tool use, retrieval, etc.)
• Strong curiosity and willingness to explore new, rapidly evolving technologies
• Bring a growth mindset, ask questions, and enjoy experimenting and iterating
• Systems thinking: able to reason about workflows, edge cases, and unintended consequences
• Clear written and verbal communication, especially when explaining technical ideas to non‑engineers
• Ownership mindset: you take responsibility for outcomes, not just tasks
• Ability to accept feedback and iterate quickly
• Familiarity with cloud environments (AWS preferred) is a plus

Desirable

• We are seeking an AI Engineering intern who will work on real AI agentic automation problems, designing, prototyping, and developing AI-powered agents to help the business and engineers achieve faster, smarter work
• You will collaborate directly with senior engineers and architects, receiving mentorship and design reviews, and gaining exposure to modern GenAI patterns, including agent orchestration, tool-calling, retrieval, and evaluation, within an enterprise and fast-paced fintech environment
• This is an opportunity to work in a collaborative, and innovative environment
• Our summer program will be 10-12 weeks from May - August 2026 with the expectation of being in the office 3-4 days per week, as determined by the sponsor
• You'll design, prototype and develop agentic AI workflows that automate or augment business or engineering tasks (e.g., analysis, triage, documentation, knowledge synthesis)
• Build internal tools or proof‑of‑concept systems that combine LLMs, APIs, and automation frameworks into end‑to‑end agentic solutions
• Experiment with different agent architectures (single‑agent vs. multi‑agent, planner/executor patterns, human‑in‑the‑loop workflows) and document tradeoffs
• Apply best practices when building AI‑driven automation
• Evaluate agent behavior for reliability, correctness, and failure modes, and propose improvements
• Clearly document designs, experiments, and lessons learned so work can be reused or extended by the team
• Demo your work directly to customers and the leadership team
• Please note: this role is expected to come into our office on a cadence set by the Hiring Manager/Team