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.

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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

software engineeringsystem designdistributed systemsdata pipelineseventingcachingAPI patternsPythondatastorescloud-native platforms

Soft Skills

leadershipstakeholder communicationmentoringcollaborationgoal settingincident managementtranslating business intenttesting culturerelease safetyroadmap transparency

Certifications

Masters in StatisticsMasters in Computer ScienceCFACPACIPMCAIAFRM