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Tier-1 brand, generalist engineering title, Bangalore location, and broad cloud/ML/compliance skillset increase competition.
Strong financial compliance and ML production requirements limit cross-industry transferability.
Mandatory 8+ years, compliance experience, and a large specific tech stack enforce strict filtering.
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Design and develop scalable, fault-tolerant microservices, APIs, and data pipelines to support compliance monitoring and detection logic for enterprise digital communications.
Operationalize ML and LLM models into detection and alert-generation pipelines, ensuring data traceability, auditability, and integration with reviewer workflows.
Lead adoption of AI-assisted engineering and SDLC automation practices across multiple teams, building CI/CD pipelines and observability tools to improve delivery speed, quality, and operational outcomes.
8+ years of experience building resilient, scalable, cloud-native enterprise products with at least 2 years in financial industry compliance.
Expertise in Java/Kotlin and Python programming, with experience building headless, externally consumable APIs.
Hands-on experience with AWS services (EC2, ECS, EKS, EMR, S3, Glacier), Elastic/OpenSearch, Kafka, PostgreSQL, and streaming frameworks like Spark or Flink.
Experience with enterprise AI-assisted development tools, observability (Prometheus, Grafana, OpenTelemetry), and CI/CD pipelines (ArgoCD, Helm, Terraform, Jenkins, GitHub Actions).
Senior-level engineer with strong expertise in cloud-native microservices and compliance-focused financial technology products.
Experienced in leading multi-team adoption of enterprise AI-assisted development and automation with governance and secure handling of sensitive data.
Skilled in operationalizing ML/LLM models and integrating observability and testing best practices for high-quality delivery and system reliability.