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Generalist senior backend title, metro location, and broad AI/Kafka requirements increase applicant competition.
Regulated-industry compliance, auditability, and pipeline experience limit cross-industry transferability.
Multiple mandatory techs (Kotlin/Java, Kafka, Prometheus) and regulated-audit constraints raise strictness.
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Deliver end-to-end AI/ML integrations within product teams, including API orchestration, workflow management, and error handling within the host codebase and release processes.
Own and scale Cognition v3 architecture involving data pre-processing, post-processing, audit subsystem, and integration pipelines handling high message volumes reliably.
Develop and maintain observability with Prometheus and Grafana, produce structured handover artifacts, and contribute to AI enablement and engineering standards including Kotlin/Java coding and architectural reviews.
Proven experience with AI/ML system integration and API orchestration in a product engineering environment.
Strong proficiency in Kotlin or Java programming languages with experience writing clean, well-tested code.
Experience with pipeline engineering patterns (Kafka, REST APIs) and observability tools such as Prometheus and Grafana.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in embedding engineering within product teams to deliver operational AI/ML workloads in compliance-focused, regulated environments.
Detail-oriented with proven ability to produce comprehensive technical documentation (architecture notes, runbooks, dashboards) and lead knowledge transfer.
Able to influence and participate in evolving engineering standards and AI productivity tooling adoption across multiple teams in a scaling technology organization.