Rapid Application & AI Development Engineer

The Equities Embedded Portfolio Management Solutions Team is looking for a hands-on Rapid Application & AI Development Engineer to build, implement, and integrate hybrid and cloud-based AI-first solutions for Fundamental and Systematic Investment Teams to accelerate their research process and productivity. You will develop, maintain, improve Python libraries, Ansible Playbooks, Terraform modules, and APIs, that are used directly by Traders, Senior Portfolio Manager, Quantitative Researcher, and Quantitative Developers.

This is a business-facing role that requires both professional business skills, engineering skills, and communication skills. An ideal candidate has a proven track record of ownership, software development lifecycle, designing and architecting enterprise-grade solutions in a fast-paced business environment. You’re proactive (never settle for status-quo), customer-centric, with the ability to establish strong relationships with stakeholders to achieve successful outcomes for the business. You are entrepreneurial, can navigate through uncertainty, extract valuable insights, and provide exceptional problem-solving for customers. You are humble, have high-integrity, and focus on what value you can provide for others instead of direct benefits you receive in return. You have an interest and passion in the buy-side hedge fund industry, machine learning, generative AI, and quantitative finance.

Principal Responsibilities

• Architect, develop and maintain hybrid and cloud application(s), libraries, and proof-of-concepts (On-prem, Google, AWS).
• Create proof-of-concepts balancing quality vs. delivery timelines to demonstrate a use-case to end-users.
• Write code, from infrastructure-as-code, software development code, data analytics scripts, machine learning samples, or automation scripts in Linux. Very likely a combination of all the above.
• Partner with Portfolio Management teams to understand their business, generate architecture ideas, build solutions, and make recommendations while considering performance, scale, costs, and maintenance complexity.
• Create re-usable assets and patterns to accelerate implementation, onboarding, and offer self-service options.
• Partner with internal teams to drive forward-momentum, remove blockers, research limitations, on behalf of the customer.
• Develop solutions for machine-learning and distributed compute use-cases in the financial industry to deploy CPU-intensive, memory-intensive, or GPU-based workloads.
• Prepare business presentations, emails, and demos working backwards from your audience, their expectations, their background, and the business outcomes for their team. You will focus on the presentation style to ensure the audience is consuming the information in the simplest form. Audience will range from technical and non-technical customers.
• Develop APIs and other managed services for investment and trading research use-cases.

Desired Qualifications

• 5-8 years of experience developing software, frameworks, libraries, and architecture patterns in hybrid or cloud environments.
• Experience in software development with Python, Java, C++, or similar object-oriented programming language.
• Experience designing and supporting production workloads in hybrid or cloud environments.
• Experience with systems engineering, including understanding of Linux security and networking.
• Experience with Infrastructure-as-code, such as Terraform, AWS Cloud Formation, or Cloud Deployment Templates.
• Experience with DevOps, including pipelines, and automation.
• Excellent ability to do root-cause analysis, troubleshooting, and analytical skills.
• Experience with data engineering (data pipelines, ETL, ELT, data warehousing) and machine learning.
• Some experience with generative AI integrating with LLMs to improve productivity, enhance product experience, or unlock new innovative features.
• Experience integrating AI in the software development lifecycle to improve software development team productivity and accelerate focus on feature development.
• Experience using AI in your own software development process, while maintaining expertise and subject matter expertise in the resulting codebase.

Preferred Qualifications

• Master’s or PhD in Computer Science, Machine Learning, or Artificial Intelligence.
• Experience with fine-tuning LLMs for business use-cases.
• Experience in customer-facing, business-facing, technical role.
• Associate or Professional-level certification in GCP or AWS (or multiple).
• Experience building technical presentations to non-technical audiences and presenting software demo
• Experience leading projects with ambiguous, possibly dynamic, requirements focus on outcomes.
• Experience leading engineers as a software development lead.