VP, Product Engineer, Alternatives

Description

The Senior Software Engineer will design, build, and operate modern applications that support investment, portfolio management, and risk workflows, with a focus on buyside/private markets use cases. The role sits at the intersection of application development, AI/ML tooling, and secure cloud‑native infrastructure.

You will own end‑to‑end product development: partnering with investment and product stakeholders, leveraging cutting‑edge AI tools (GenAI, copilots, agents, MLOps), and taking responsibility for core applications from architecture and implementation through Dev Ops and Dev Sec Ops .

The ideal candidate combines strong hands‑on software engineering skills with a product mindset, investment management domain familiarity, strong communication, and the ability to independently drive strategic initiatives in a complex, regulated environment.

• Collaborate with security and infrastructure teams to address vulnerabilities, harden services, and maintain a strong security posture for sensitive financial and client data.
• Product Management & Stakeholder Engagement
• Partner closely with investment professionals (e.g., portfolio managers, private markets deal teams), operations, risk, and technology stakeholders to understand workflows, pain points, and opportunities.
• Translate ambiguous business and investment requirements into clear technical roadmaps, user stories, and iterative deliverables with measurable outcomes.
• Prioritize and manage a backlog of application features and technical enhancements, balancing short‑term value with long‑term architectural health.
• Communicate trade‑offs, timelines, and architecture decisions clearly to both technical and non‑technical stakeholders.

• Serve as a technical lead on key initiatives, setting engineering standards and reviewing designs and code for quality, performance, security, and operational readiness.
• Mentor engineers across the team in best practices for software design, Dev Ops, Dev Sec Ops , and cloud‑native development.
• Drive continuous improvement in development workflows, testing strategies, release management, and incident management processes.

• 5+ years of professional software engineering experience, with significant time spent building and operating production applications and services.
• Strong proficiency in Python and at least one additional language commonly used in modern back‑end or platform development (e.g., C#, .Net, Go, Rust, or Scala).
• Hands‑on experience designing and delivering business‑critical applications end‑to‑end (architecture, implementation, testing, deployment, monitoring, and support).
• Practical familiarity with investment management workflows (e.g., research support tools, portfolio or risk dashboards, order and execution workflows, or private markets deal and pipeline management).
• Experience with cloud‑native development and containers (e.g., Docker, Kubernetes), including deploying and operating services in production.
• Solid experience with CI/CD and modern Dev Ops practices (Git‑based workflows, automated testing, infrastructure as code, monitoring/logging).
• Demonstrated involvement in secure development practices or Dev Sec Ops , such as integrating security scanning into pipelines or working closely with security teams.
• Strong SQL skills and experience working with large analytical datasets and data warehouses/data lake houses.
• Proven ability to interface directly with business and product stakeholders, gather requirements, and deliver solutions end‑to‑end.
• Excellent written and verbal communication skills, including the ability to explain complex technical concepts in clear, accessible language.

• Advanced degree in Computer Science, Engineering, Information Systems, or a related technical field.
• Direct experience in buyside or private markets environments (e.g., asset management, hedge funds, private equity, private credit, real assets).
• Experience building or evolving modern data lakehouse architecture (e.g., Parquet, Apache Iceberg or Delta Lake, Trino, Dremio).
• Hands‑on experience with Data Ops and MLOps tools (e.g., Airflow, Prefect,…