Senior Manager, Investments Technology

Role Overview

• Own the Vision technical roadmap : set architectural direction, prioritize platform investments, and align with business outcomes in Asset Allocation, Custom Equities/Indexes, Global & Quant Strategies.
• Lead a high‑performing engineering team : hire, mentor, and manage engineers; establish clear goals; ensure reliable, predictable delivery.
• AI‑accelerated engineering : institutionalize daily use of AI tools (e.g., GitHub Copilot, Claude, ChatGPT, AWS Bedrock) for coding, tests, documentation, and prototyping; set review standards for AI‑generated code.
• API & data platform leadership : own domain services, API design & caching, and high‑scale ETL (e.g., Morningstar, MSCI ESG, Aladdin, Bloomberg, RIMES) with strong SLAs, observability, and governance.
• Quality & reliability : raise the bar on unit/integration testing , CI/CD, rollout/rollback patterns, SLOs, on‑call hygiene, and incident postmortems.
• Cloud cost & performance (FinOps) : drive right‑sizing, archiving, workload scheduling, and cost observability to continuously reduce $/feature.
• Security & compliance : ensure platform and AI usage adhere to enterprise security, privacy, and model‑risk standards.
• Stakeholder partnership : collaborate with investment professionals, research, data, and product to translate business intent into technical outcomes.
• SRE collaboration : partner with the SRE Manager on reliability, infra automation, and uniform standards across environments.
• Roadmap transparency : maintain a clear backlog, delivery plan, and communication cadence to business partners and leadership.

Requirements

• 10+ years in software engineering with 3–5+ years leading teams as an engineering manager or senior manager delivering cloud‑native platforms.
• Proven system design expertise (distributed systems, data pipelines, eventing, caching, API patterns) and experience running mission‑critical services in production.
• AI‑assisted development fluency : daily use of AI tools for coding, test generation, refactoring, documentation, and design exploration—plus the ability to evaluate/correct AI‑generated code for security, performance, and maintainability.
• Hands‑on depth in Python (data/ETL frameworks, performance profiling), datastores (SQL + NoSQL), and cloud (AWS) including containerization (Docker) and CI/CD.
• Track record improving observability (logging, metrics, tracing), testing culture , and release safety (feature flags, canaries, rollbacks).
• Strong stakeholder communication; able to translate investment workflows into reliable, scalable technical solutions.
• Experience with LLM/AI service integration (e.g., AWS Bedrock, Anthropic Claude, OpenAI APIs), retrieval/embeddings , and prompt engineering patterns in real products.
• Familiarity with fin/quant data and portfolio analytics; comfort partnering with research and data science.
• Background with FinOps tooling and cost‑aware architecture.
• Masters in Statistics, Computer Science or other similar advanced degrees from a top tier educational institution preferred
• CFA, CPA, CIPM, CAIA, and/or FRM preferred, but not required.

Tech Stack

• AWS
• Cloud
• Distributed Systems
• Docker
• ETL
• NoSQL
• Python
• SQL

Benefits

• Flexible paid time off
• Hybrid work schedule
• 401(K) matching of 100% up to the first 6% with a discretionary supplemental contribution
• Health & wellbeing benefits
• Parental Leave benefits
• Employee stock purchase plan