Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 8+ years applied experience
In-depth knowledge of the financial services industry and their IT systems
Hands-on practical experience delivering system design, application development, testing, and operational stability along with proficient in all aspects of the Software Development Life Cycle
Advanced in one or more programming language(s) and practical cloud native experience
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Strong proficiency in Java with appropriate concurrency tooling, and proven experience developing multi-threaded components and concurrency-safe services (thread pools, async pipelines, and lock-free structures where appropriate)
Strong troubleshooting skills using profilers, thread dumps, heap analysis, and production telemetry, with a proven ability to diagnose and resolve concurrency issues such as deadlocks, race conditions, starvation, and memory visibility problems
Design, implement, and operate event-driven architectures using a message bus (pub/sub, queues, streams), and optimize throughput and latency for message processing through batching, backpressure, partitioning, and consumer groups
Preferred qualifications, capabilities, and skills
Proven experience with one or more message bus technologies such as: AMPS, Kafka, IBM MQ, TIBCO, RabbitMQ, ActiveMQ, etc.
Implement observability for distributed processing (structured logs, metrics, tracing; lag/offset monitoring).
Write robust automated tests (unit, integration, contract tests; concurrency and load tests).
Familiarity with schema management (Avro/Protobuf/JSON Schema) and API/message versioning strategies.
Experience with containerized deployments and orchestration (Docker, Kubernetes).
Observability: OpenTelemetry, Prometheus/Grafana, ELK/Splunk
CI/CD: GitHub Actions/Jenkins, automated integration environments
