Lead Software Engineer - Backend Java, Markets Tech

Overview In this Lead Software Engineer role, you contribute as a core technical leader in an agile team building secure, scalable, market-leading technology products. You’ll deliver high-quality production code and drive modern architecture across distributed microservices. You will integrate AI/ML and GenAI capabilities into core platforms at enterprise scale, while ensuring governance and reliability. You collaborate with business, product, and operations teams to translate Prime Finance and Broker Dealer needs into scalable solutions, shaping the platform’s evolution. Compensation / Benefitscomprehensive health care coverageretirement savings plantuition reimbursementmental health supporton-site health and wellness centersbackup childcare ResponsibilitiesDevelop secure, high-quality production code and perform reviews to ensure engineering excellenceBuild and integrate AI/ML and GenAI into production platforms (LLMs, RAG, embeddings, vector stores, MLOps) and establish governance and monitoringDrive enterprise AI-assisted engineering practices, including code review, testing automation, and incident analysisIdentify and automate remediation of recurring issues to improve stability and performanceLead architectural and design decisions for scalability and long-term platform evolutionEvaluate architecture with internal teams to ensure alignment with enterprise strategiesContribute to platform modernization through cloud-native, event-driven, and microservices-based approachesProvide technical leadership and mentorship to engineers, fostering a collaborative culturePartner with business, product, and operations to translate requirements into scalable solutionsEnsure robust delivery with strong SDLC, testing, and production stability Key requirements5+ years of applied software engineering experienceAdvanced proficiency in Java, Spring Boot and REST APIs within microservicesExperience with relational databases (Oracle/DB2) and/or NoSQL (MongoDB)CI/CD, DevOps, and automation practicesProficiency across the Software Development Life Cycle (SDLC)Strong problem-solving, analytical, and stakeholder communication skillsProven ability to build high-volume, low-latency, mission-critical financial systemsHands-on experience integrating AI/ML and GenAI into enterprise apps (LLMs, RAG, embeddings, vector stores, MLOps)Experience leading use of AI-assisted software development tools and setting team expectations for AI outputsproblem-solvingstakeholder communicationleadership and mentorshipAI/ML and GenAI integration (LLMs, RAG, embeddings, vector databases, MLOps)Cloud-native development (AWS or equivalent)Event-driven architectures (Kafka, MQ)