• Provide overall direction, oversight, and coaching for a team of entry-level to mid-level software engineers that work on basic to moderately complex tasks.
• Provide architectural oversight for Java‑based enterprise platforms with a focus on performance, reliability, security and operability.
• Lead modernization across legacy, cloud, and hybrid environments; enforce secure design and compliance guardrails.
• Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets.
• Provide direction, oversight, and coaching for entry‑ to mid‑level engineers; grow talent and raise engineering standards.
• Ensure successful collaboration across teams and stakeholders; align product, engineering, operations, and risk on priorities and outcomes.
• Lead incident response and root‑cause analysis; drive corrective and preventive actions to improve stability.
• Provides input to leadership regarding budget, approach, and technical considerations to improve operational efficiencies and functionality for the team.

• Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, 2 + years of experience leading technologists to manage and solve complex technical items within your domain of expertise.
• Experience with hiring, developing, and mentoring talent and guiding team to deliver against a set of strategic initiatives.
• Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns.
• Strong hands-on experience in Java‑based platforms and other languages like Spring Boot, React, Python operating in production at scale.
• Expertise in core Java, Spring Boot, J2EE, messaging systems (MQ), Oracle, Postgres, DAPR, Flink, Kafka and Apache Iceberg.
• Proficient in UNIX, Apache Tomcat, Web Services, and SQL; knowledge of Java Script framework is must
• Experience with high‑volume transactional and batch systems.
• Practical cloud‑native engineering and operating in hybrid deployments within regulated environments.
• Familiarity with SDLC, secure development practices, and compliance controls for regulated platforms.
• Ability to communicate complex technical topics clearly to senior stakeholders across Product, Engineering, and Operations.

Preferred qualifications, capabilities and skills

• Financial industry experience is highly desirable.
• Experience working at code level.