Financial Services Technology Consulting, Financial Risk Technology (FRT) Engineering - Manager

EY•Atlanta, GA

1d•$142,600 - $297,200•Hybrid

About The Position

Our Financial Services ("FSO") teams help clients address complex transformation priorities across Banking, Insurance and Capital Markets. This opportunity combines Insurance Risk, Credit Risk and Capital Markets technology expertise with modern engineering to deliver high-impact enterprise transformation programs. Financial institutions are modernizing risk, finance and trading platforms to improve scalability, transparency, control and responsiveness. The role spans cloud-native risk platforms, analytical and model-execution engines, regulatory and actuarial processing, and front-to-back modernization across front-office, middle-office and back-office functions. Key capabilities include pricing and positions, pre-trade and counterparty risk, Value at Risk (VaR), stress testing, sensitivities, XVA, clean P&L, hypothetical P&L, actual P&L, P&L attribution, settlement, reconciliation and regulatory reporting. As a Manager, you will lead solution architecture and engineering delivery, guide globally distributed teams, and work directly with business stakeholders, traders, risk leaders, actuaries, model developers, operations teams and technology executives. You will translate complex business, regulatory and analytical requirements into practical target-state architectures and production-grade solutions spanning trading, risk, finance and operations.

Requirements

Strong combination of risk-domain knowledge, solution architecture and hands-on engineering expertise.
Ability to lead complex workstreams, communicate trade-offs and influence senior business and technology stakeholders.
Proven ability to structure ambiguous problems and convert them into executable roadmaps and delivery plans.
Strong written and verbal communication, presentation, client service and technical writing skills.
Insurance Risk Management
Actuarial Modeling Platforms
Reserving and Capital Models
Solvency Frameworks
Risk Aggregation and Reporting
Insurance Data Platforms
Reinsurance Processing
CECL / IFRS 9
Credit Portfolio Analytics
Probability of Default (PD)
Loss Given Default (LGD)
Exposure at Default (EAD)
Credit Stress Testing
Regulatory Capital
Counterparty Credit Risk
Basel Frameworks
CCAR
CECL
FRTB
Basel III / IV
XVA
Market Risk
Liquidity Risk
Asset and Liability Management (ALM)
Front-office trading, pricing, position management and pre-trade risk platforms
Middle-office risk, controls, trade validation, valuation and P&L processes
Back-office confirmations, settlement, accounting, reconciliation and regulatory reporting
Value at Risk (VaR), stress testing, sensitivities and market-risk analytics
XVA, including counterparty credit and funding valuation adjustments
Clean P&L, hypothetical P&L, actual P&L and P&L attribution
Front-to-back modernization and integration across trading, risk, finance and operations
Java (advanced or expert proficiency)
Python
Scala and/or C++
Spring Boot and REST APIs
Object-oriented design and design patterns
Multithreaded development
High-performance computing
DAG-based workflow engines
Distributed architectures and grid computing
Parallel and large-scale batch processing
Risk calculation platforms
Event streaming and pub/sub architectures
Apache Kafka, AWS MSK and/or Azure Event Hubs
Event-driven design patterns
AWS: ECS, EKS, Lambda, S3, DynamoDB, EC2, AWS Batch and CloudFormation
Azure: Azure Kubernetes Service, Azure Event Hubs, Azure Data Lake and Azure Functions
MongoDB
PostgreSQL
SQL Server
Oracle
Apache Spark
Databricks
Distributed data processing
Data governance
Data reconciliation
Risk data warehousing
Docker
Kubernetes
GitHub
CI/CD pipelines
Terraform
Infrastructure as Code
8+ years of software engineering experience, including 5+ years designing or delivering risk technology solutions.
Proven delivery experience in Insurance, Banking or Capital Markets.
Strong understanding of Credit Risk, Insurance Risk and applicable regulatory frameworks.
Experience building cloud-native risk platforms at enterprise scale.
Demonstrated experience leading architecture and engineering teams while engaging effectively with business stakeholders and executives.
Experience leading distributed teams and complex technology delivery across multiple workstreams.
Undergraduate or graduate degree in computer science, engineering, mathematics, actuarial science, finance or a related field.

Nice To Haves

Prior consulting experience is preferred.
Capital Markets products and front-to-back trade lifecycle knowledge
Front-office trading systems, including pricing, positions and pre-trade risk
Distributed computing and high-performance processing architectures
Advanced Java development, including multithreading and concurrency
Databricks and/or Snowflake data platforms
Redis and/or GridGain-style distributed caching solutions
Agentic AI and risk automation
Retrieval-Augmented Generation (RAG) architectures
LangChain
Model Context Protocol (MCP) frameworks

Responsibilities

Lead the architecture, modernization and implementation of Insurance and Credit Risk platforms.
Define target-state architectures and practical modernization roadmaps for risk and finance platforms.
Lead front-to-back modernization of Capital Markets platforms across front-office trading and pricing, middle-office risk and controls, and back-office settlement, accounting and reconciliation.
Own architecture for VaR, stress testing, sensitivities, XVA, counterparty risk, clean P&L, hypothetical P&L, actual P&L and P&L attribution capabilities.
Own solution design across Credit Risk Management, CECL / IFRS 9, CCAR stress testing, Expected Credit Loss, portfolio analytics, capital and regulatory reporting, insurance modeling and reserving, and liquidity or balance-sheet risk.
Collaborate with risk business teams to translate regulatory, actuarial and analytical requirements into scalable technical solutions.
Design and build cloud-native platforms supporting large-scale model execution and risk calculations.
Lead distributed computing, workflow orchestration and event-driven architecture initiatives.
Drive performance optimization of analytical and risk-processing engines.
Establish standards for resiliency, scalability, observability, security and operational excellence.
Design enterprise data models supporting Insurance and Credit Risk calculations.
Lead data integration frameworks across risk engines, data lakes and operational systems.
Enable lineage, governance, auditability and reconciliation capabilities for risk data.
Lead globally distributed engineering teams and coordinate delivery across architecture, development, data and platform workstreams.
Mentor architects, developers and risk technology professionals.
Drive technical governance, architecture reviews, engineering standards and delivery quality.
Collaborate with client executives and senior stakeholders on technology strategy, delivery planning and risk management.