Senior Product Architect – Front-to-Risk Platform

Numerix

Greater London

Hybrid

GBP 120,000 - 180,000

Full time

10 days ago
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Job summary

Numerix is seeking a Product Architect, Oneview Engineering, to bridge business intent with technical execution. You will translate complex product requirements into robust, scalable designs and partner with Product Management, Business Analysis, and Engineering to ensure delivery readiness.

In this senior role reporting to Engineering leadership, you will shape architecture across Oneview modules, define interfaces, and guide teams towards reusable, scalable solutions while evaluating AI

Qualifications

  • Bachelor's degree in Finance, Mathematics, CS, Engineering or related field; advanced degree or CFA/FRM/PRM is a plus.
  • 10+ years of experience in financial technology, capital markets software, quantitative analytics, product development, financial engineering, business analysis, solution architecture, or related field.
  • Strong understanding of derivative trade lifecycle from front/middle/back-office perspective.
  • Familiarity with pricing, valuation, risk, P&L, VaR, stress testing, market data, reference data, security master, trade capture, position management, and related workflows.
  • Knowledge of financial product structures, curve building, valuation models, risk analytics across asset classes (FI, Credit, Equities, Commodities, FX).
  • Experience translating business needs into functional/technical requirements.
  • Proficiency with APIs, databases, data integrations, cloud services, microservices, and delivery processes.
  • Ability to work credibly with engineers, product managers, analysts, financial engineers, and client-facing teams.
  • Strong analytical skills to decompose complex information and resolve ambiguities.
  • Intermediate scripting or prototyping in Python to support solution development.
  • Excellent written and verbal communication to document decisions, trade-offs, risks.
  • Ability to operate in a fast-paced, multi-geography product environment.
  • Detail-oriented with ownership mindset and ability to manage multiple deliverables.

Responsibilities

  • Translate business and product requirements into end-to-end solution designs.
  • Decompose features into implementable solutions, identifying rules, dependencies, edge cases, and risks.
  • Drive development readiness by refining requirements, user stories, flows, and acceptance criteria.
  • Produce design artifacts, workflow definitions, dependency maps, and interface specs for implementation.
  • Steward Oneview's product architecture, ensuring clear ownership, boundaries, APIs, and reusable components.
  • Evaluate impact across data models, analytics, workflows, integrations, and deployment paths.
  • Address non-functional requirements including scalability, performance, maintainability, and SaaS readiness.
  • Collaborate across Oneview modules and Numerix products for end-to-end optimization.
  • Facilitate design discussions and decision-making across teams to reduce ambiguity.
  • Influence AI strategy by evaluating capabilities and aligning with product direction.
  • Stay current with architecture, product platforms, and market trends.

Skills

Fintech experience
Derivative lifecycle
Python scripting
APIs & data integrations
Cloud services
Microservices
Architectural leadership
Cross-functional collaboration
Communication skills
Problem decomposition

Education

Bachelor's degree in Finance/CS/Engineering
Advanced degree or CFA/FRM/PRM (plus)

Tools

APIs
Databases
Cloud platforms
Data models

Job description

Numerix is seeking a Product Architect, Oneview Engineering, to bridge business intent with technical execution. You will translate complex product requirements into robust, scalable designs and partner with Product Management, Business Analysis, and Engineering to ensure delivery readiness.

In this senior role reporting to Engineering leadership, you will shape architecture across Oneview modules, define interfaces, and guide teams towards reusable, scalable solutions while evaluating AI

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