About the role

Aplyr's Quick Take

This role is for a Technical Program Manager focused on managing the development lifecycle of C++ systems in a high-performance environment. You'll lead Agile processes, manage project timelines, and facilitate communication between engineering teams, ensuring smooth execution without getting into coding yourself.

Good fit

Ideal candidates have 5+ years in program management or a similar role within tech-heavy industries like FinTech or HFT. A strong understanding of C++ development and Agile methodologies is essential, along with the ability to communicate complex technical issues clearly.

Worth noting

The role emphasizes a deep understanding of low-latency systems and requires advanced skills in Jira and Confluence. It's a hands-off management position, focusing more on orchestration than direct coding.

Role Overview

We are looking for a Program Manager who thrives at the intersection of rigorous engineering and predictable delivery. You will not just "manage tasks", you will orchestrate the development lifecycle for mission-critical C++ systems. Your goal is to ensure that our elite engineering teams can focus on high performance code while you own the execution strategy, dependency mapping, and release discipline.

Key Responsibilities

Lead Agile ceremonies (Sprint Planning, Stand-ups, Retrospectives) tailored for deep-tech systems programming.
Transform high-level trading requirements into granular, executable backlogs. Own capacity planning and burn-down metrics to provide high-visibility delivery timelines.
Navigate the complex interplay between Connectivity (Market Data/Order Entry), Core Infrastructure, and Simulation teams to prevent bottlenecks.
Build and maintain advanced Jira dashboards, automated roadmaps, and Confluence documentation that serve as the "single source of truth" for stakeholders.
Proactively identify technical debt, architectural blockers, or resource gaps that threaten release stability.
Continuously refine Agile methodologies to suit low-latency C++ development cycles (where "Definition of Done" includes rigorous performance benchmarking).

Eligibility & Required Skills

5+ years of experience as a TPM, Program Manager, or Scrum Lead in a product-engineering environment (HFT, FinTech, Networking, or Kernels/Systems).
A strong grasp of the C++ development lifecycle. While you won't write code, you must understand concepts like build systems, CI/CD for systems software, and performance regressions.
Expert-level proficiency in Jira Service Management/Software and Confluence. Ability to use JQL for advanced reporting.
Exposure to low-latency, trading systems, networking, or infra software preferred.
Exceptional ability to translate complex technical constraints into clear business updates for Engineering Leads and Partners.

Skills & Tags

go ai data product

Aplyr's read

Graviton Trading is a dynamic proprietary trading firm where quantitative minds and tech-savvy professionals thrive in fast-paced financial markets.
Synthesized from recent postings & public sources

What's promising

•Graviton offers a tech-driven environment with a focus on innovative quantitative trading strategies.
•The firm provides diverse opportunities in global financial hubs like Amsterdam and Singapore.
•Graviton emphasizes cutting-edge technology, attracting skilled software engineers and quantitative researchers.

What to watch

•The competitive nature of proprietary trading can lead to high-pressure work environments.
•Limited public information about Graviton's long-term financial stability and market position.
•Potential candidates may face intense competition for roles due to the firm's niche focus.

Why Graviton

•Graviton specializes in market-making across diverse asset classes, setting it apart from other trading firms.
•The firm's integration of high-performance computing in trading strategies is a distinctive feature.
•Graviton's focus on quantitative research and technology-driven solutions differentiates it from traditional finance firms.

Aplyr’s read is generated by AI from public sources. Was it useful?