Job Description:

Director, Software Engineer – Asset Management Technology

The Role

You are an experienced engineering lead with a deep hands on experience of systems development, and a burning desire to unlock the capabilities of GenAI implementation in the context of a professional domain such as finance. You are excited about this opportunity to help lead an applied technical group conceiving of, building and delivering first-of-a-kind knowledge-based applications for investment professionals.

You have prior experience in developing and designing to deliver production applications using rapidly evolving, powerful yet brittle AI technology. You are comfortable working in a quick time to market technical area where the lag between conceptualization, research and development, and productionization is optimized. You are skilled at working with senior business, architecture and engineering stake-holders, mentoring junior individual contributors, helping them grow and learn new skills in today’s fast-paced AI field. You possess excellent thinking process and technical skills and revel in working as part of a team to solve deep applied problems.

You will have:

• A Bachelor’s or Master's Computer Science or relevant field (with a background in Machine learning is a plus), with ten years plus of industrial experience.
• An understanding of how to deliver into production GenAI applications that can reliably process information in open-ended settings
• Adept in Python as the enterprise level development language.
• Mastery of design patterns and object-oriented programming techniques.
• Strong understanding of best practices for large scale application design, SOA, microservices, distributed compute, containers, and use of the cloud.
• Strong attention to detail, passion for careful and automated testing.
• Excellent communication skills and ability to work with distributed team members
• A track record of managing the "exploration vs exploitation" tradeoff to deliver innovative solutions for first-of-a-kind problems.

The Team

We are developing a Large Language Model (LLM)-first knowledge stack for investment professionals at Fidelity Asset Management – analysts and portfolio manager in equities, fixed income, high income, direct lending. The stack will be able to process all the documents of interest to analysts – e.g., analyst reports, earnings notes, spreadsheet models, prospectuses, loan indentures, news reports, regulatory filings. It will support the deployment of personalized assistants that can assist principals in their full range of information consumption/processing/production tasks.

Certifications: