Software Engineer
US$125,000 – US$160,000 / yr base salary
Posted 27 Feb 2026
Advertised as “Senior Associate, Software Engineer – Data Platform & AI Applications”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5–8 yrs
- Management level
- Individual contributor
| Base salary | US$125,000 – US$160,000 / yr |
|---|
Study levelBachelor's
Jordan Park provides investment management and financial advice to a distinct community of individuals, families, and institutions. Our clients have made extraordinary contributions to business, philanthropy, government, and society. Our team is composed of empathetic problem solvers with depth and diversity of experience. We embrace complexity and navigate challenges to empower clients to achieve their optimal outcomes.
Our mission is to enhance lives and legacies.
**Senior Associate, Software Engineer – Data Platform & AI Applications
**San Francisco, California
The Opportunity
Jordan Park is seeking a Senior Associate to help build and extend our enterprise data platform and AI application ecosystem.
This role combines advanced data engineering, cloud infrastructure, DevOps discipline, and applied AI development. The Senior Associate will operate as a senior individual contributor — owning major platform components while partnering closely with leadership and business teams. This is a hands-on technical role with meaningful scope and influence.
In this role, you will be responsible for enabling trusted analytics across the firm, integrating proprietary data into AI systems, automating operational workflows and creating custom apps and tooling.
Your Role
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Data Platform Engineering
- Design, build, and maintain production-grade SQL data pipelines (e.g., dbt + Snowflake + Python)
- Develop and manage orchestration workflows (Airflow or equivalent)
- Create data ingestion processes and API integrations
-
AI Application Development
- Build and develop the use of AI in the form of: LLM apps, RAG architectures, Custom GPTs & Agent systems
- Integrate proprietary firm data securely into AI workflows
- Establish observability standards
- Translate AI experimentation into production-grade tools
-
Cloud Infrastructure (AWS)
- Support AWS-based infrastructure including VPCs, ECS, EKS, S3, etc.
- Containerize services using Docker and manage workloads in Kubernetes
- Establish logging, monitoring standards
-
Python Development & Automation
- Develop Python-based tools for API integrations, data transformations, ad-hoc in-house applications & tooling
- Build reusable modules and maintain code standards