Requirements

Significant hands-on experience designing, building, and running production applications in large corporate environments
Deep proficiency in at least one programming language and comfort working across the stack
Strong systems thinking with the ability to design solutions that fit across platforms, data flows, and teams
Practical, regular use of AI tools in engineering, with sound judgement for reviewing AI-generated code
Working understanding of agentic systems including tool usage, API integration, workflow orchestration, and observability
Business-first approach to problem solving with strong judgement to identify problems worth solving
Proven track record of building trusted relationships with senior business stakeholders and accountability for delivery
Clear and candid written and verbal communication skills, including delivering difficult messages to senior audiences
Comfortable collaborating across teams to resolve problems and bring people together as needed
Experience guiding and reviewing the work of other engineers
Demonstrated accountability for outcomes of both individual and team work
Confidence to challenge the status quo and a habit of continuous improvement

Nice to Haves

Proficiency in Python (primary language)
Understanding of financial markets and Market Risk concepts such as sensitivities, VaR, Stress, or FRTB
Familiarity with Athena or SecDB and related integration patterns
Experience with Databricks or similar data platforms
Experience building LLM-based or agentic capabilities in production environments (e.g., retrieval, tool interfaces, multi-agent orchestration)
Experience leading a small team of engineers

Design, build, and run end-to-end production applications including services, data pipelines, and user interfaces integrated with firm platforms and data sources
Understand business problems behind requests and shape solutions accordingly, sometimes proposing alternative approaches
Identify underlying problems worth solving and advocate for them
Design solutions considering system-wide impact, balancing speed, resilience, and maintainability
Create applications, APIs, and data suitable for AI agents as well as human users, ensuring clear interfaces and proper controls
Build trusted relationships with senior Market Risk stakeholders and remain accountable for delivery
Set clear expectations on scope, success criteria, timelines, and risks while maintaining open communication
Provide transparency on project status, raise issues early, and present options for resolution
Collaborate across teams to resolve challenges, facilitating conversations and follow-through
Guide and review junior engineers' work, supporting their growth in skills and judgement
Leverage AI tools daily to enhance build, test, and documentation processes and explore AI-driven business problem solutions
Challenge and improve existing processes and tools, retaining those that add value
Uphold high engineering standards in design, coding, testing, CI/CD, security, observability, documentation, and runbooks
Represent the team to senior stakeholders, lead by example, and contribute to an inclusive and respectful team culture

Opportunity to be a key technology partner to senior Risk Managers
Work on impactful problems that matter to the business
Chance to develop solutions that remain robust as business needs evolve
Exposure to cutting-edge AI tools and agentic system design
Influence on improving team processes and tools
Supportive environment for mentoring and growing junior engineers
Recognition and representation as a leader within the team and broader organization