• You will own the technical design and delivery of backend services, APIs, data integrations, and reusable libraries within an assigned domain.
• You will translate ambiguous requirements into architecture options, estimates, sequencing, and clear acceptance criteria.
• You will set and uphold standards for automated testing, code quality, secure coding, performance, and operational readiness.
• You will build observability, structured logging, alerting, and failure handling into services so that issues are detectable before users report them.
• You will lead code and design reviews, mentor engineers, and raise the overall technical capability of the team.
• You will diagnose complex production incidents, drive root-cause analysis, and deliver systemic fixes rather than point remedies.
• You will partner with product, architecture, data, and Legal, Risk and Compliance to ensure solutions meet enterprise security and control requirements.
• You will maintain high- and low-level technical documentation and evaluate new tools and approaches against measurable delivery value.
Strategic Responsibilities
• You will approach system design, architecture, or technical decisions by considering where AI can meaningfully improve the solution, not just the development process.
• You will evaluate trade-offs between AI-assisted and traditional approaches with practical judgement.
• You will identify repetitive, manual, or error-prone processes in the team's work and introduces AI-powered improvements, including code reviews, AI-assisted testing, intelligent alerting, or document generation.
• You will apply advanced prompting techniques to tackle ambiguous, multi-step, or domain-specific problems.
• You will think through how AI-assisted solutions will be tested, deployed, monitored, and maintained.
Technical Environment
• Core stack: Python, SQL, modern backend services and APIs, with supporting data-processing and testing libraries.
• Operating environment: Cloud or hybrid environments, containerized services, secure enterprise data integrations, and approved model endpoints.
• Workflow: Git-based development, CI/CD, automated testing, agile delivery, and infrastructure or configuration as code.
• Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.
• 5+ years of professional software engineering experience, including production backend, distributed, or data-intensive systems.
• Demonstrated experience with automated testing, CI/CD, containerization, observability, secure coding, and operational support.
• Track record of leading technical design for non-trivial features and mentoring other engineers.
• Experience in asset management, wealth management, portfolio analytics, trading, or risk technology would be a plus.
• Hands-on experience with LLM applications, AI agents, retrieval-augmented generation, or model evaluation would be a plus.
• Experience with cloud platforms, Kubernetes, workflow orchestration, event-driven systems, or time-series data would be a plus.
• Experience moving data-science prototypes into secure, supportable production services would be a plus.
Technical Skills
• Advanced Python skills and strong experience with APIs or microservices, SQL, data processing, software design, and system integration.
Soft Skills
• Strong written and verbal communication skills, sound technical judgement, and the ability to collaborate across engineering, product, and control functions
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