Senior Lead Software Engineer

Responsibilities

• Provide technical guidance and direction to technical teams, contractors, and vendors.
• Develop, review, debug, and maintain secure, high-quality production code.
• Drive governance and adoption of AI-assisted engineering practices, including validation standards for correctness, performance, security, testing, and release readiness.
• Own architecture and solutioning for Trust & Security data and integration capabilities, including proofs of concept, reference architectures, target-state roadmaps, and migration paths.
• Design and implement reliable, scalable Kafka streaming solutions with ordering, idempotency, replay, dead-letter queues, schema governance, and operational readiness.
• Build streaming and batch data publishing patterns for lake and analytical platforms with observability, data quality checks, lineage, metadata, and access controls.
• Lead solution engineering for Java services, pipelines, and streaming or processing components.
• Architect Cassandra and Oracle data stores, including partitioning, performance, consistency, resiliency, schema design, SQL performance, and integration patterns.
• Design REST and GraphQL service interfaces and integrations with API and error contracts, SLAs/SLOs, and backward-compatible change practices.
• Establish engineering standards, reuse-first patterns, responsible AI usage, and compliant validation controls across teams.

Requirements

• Formal training or certification in software engineering concepts and at least 5 years of applied experience.
• Hands-on experience delivering system design, application development, testing, and operational stability.
• Advanced expertise in one or more of Java, Kafka, Spark, or Flink.
• Experience combining data architecture and solution engineering in large-scale production environments.
• Hands-on experience with Kafka, streaming or batch publication to data lakes or platforms, Cassandra, Oracle, and Java services or pipelines.
• Experience designing schema registries, data contracts, and data governance practices.
• Experience building APIs and integrations with REST and GraphQL.
• Strong SDLC discipline, including testing strategy, code review, production support, observability, and automation.
• Ability to work independently with little-to-no oversight and demonstrate strong problem-solving and rapid learning skills.
• Experience leading enterprise-authorized AI-assisted software development practices and validating AI outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity, secure input and output handling, resiliency, and security expectations.
• Preferred experience in Trust & Security domains such as fraud, IAM, device trust, cyber signals, third-party risk, or data loss prevention.
• Preferred experience with Kafka Streams, Flink, Spark Streaming, real-time enrichment or correlation, AI/ML concepts, feature stores, AWS ecosystems, cloud-native modernization, graph databases, or TigerGraph.
• Track record of setting engineering standards and driving reuse across teams without direct people management.

Benefits

• Competitive total rewards package with base salary determined by role, experience, skill set, and location; eligible roles may also receive commission-based pay or discretionary incentive compensation.
• Comprehensive health care coverage and on-site health and wellness centers.
• Retirement savings plan, backup childcare, tuition reimbursement, mental health support, and financial coaching.
• Additional compensation and benefits details are provided during the hiring process.