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PMGTech leads PMG’s AI strategy by building an AI-ready research environment, unified data layer, agentic orchestration networks, and an investment-focused application layer to deploy AI-powered research solutions into production. As part of PMGTech, you will work directly with investment researchers and portfolio managers to build and scale capabilities in data engineering, GenAI, and platform tooling, streamlining research workflows and enabling differentiated, alpha-generative investment insights across PMG’s investment pillars.
Job Responsibility:
Design architectures for AI-powered research applications leveraging Generative AI capabilities (RAG, agentic workflows, search, model fine-tuning)
Partner with investors to translate open-ended research questions into feasible AI-driven product concepts
Be hands-on in leading the lifecycle from POC to MVP to production for AI applications, including data pipelines and backend integration
Own the end-to-end user experience of investor-facing research apps, including intuitive front-end UI designs
Evaluate emerging models and APIs
define best practices for prompts, safety, reliability, and testing with internal and external tech teams
Leverage enterprise data engines, orchestration frameworks, and secure/observable production practices with Engineering Hub and Platforms
Implement monitoring, observability, evaluation frameworks, and data-quality safeguards for GenAI-powered research applications
Requirements:
Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or equivalent
6+ years of work experience delivering ML, AI, and data-intensive systems
Hands-on experience building and deploying AI systems end-to-end - including LLM workflows, prompt engineering, RAG pipelines, entity extraction, embeddings/vector search, text2sql, fine-tuning, evaluation, and backend integration using Python and SQL
Strong written and oral communication skills and ability to work directly with investors and senior partners is a must
Nice to have:
Domain specific experience is a plus - building data-driven / research applications for investment research, investment management or financial services
Hands-on experience with any major cloud platform, proficiency in front-end or full-stack development is a plus
Preference for prior experience with open-source language models and actively staying current with developments in the rapidly evolving generative AI landscape
Understanding of investment strategies and asset classes is a plus