The role
We’re hiring a Senior Engineering Manager to lead our Java-based platform teams. You’ll own delivery, reliability, and technical growth across mission-critical payment APIs and microservices. This is a hands-on leadership role combining architecture, people management, and operational excellence.
What you’ll do
Lead and grow multiple engineering teams, including hiring, performance management, and career development.
Drive architecture and design for microservices, APIs, and payment integrations.
Ensure system reliability, scalability, security, and compliance with payment standards.
Champion engineering best practices: CI/CD, automated testing, code reviews, observability.
Own system reliability, capacity planning, and SLOs for both transactional services and ML inference workloads; optimize cost and latency trade-offs.
Partner with Product, Data & AI Engineering, Risk, Security, and Compliance to prioritize initiatives, embed models into workflows, and ensure regulatory readiness.
Establish KPIs for engineering and AI (lead time, MTTR, model drift, inference latency, false positive/negative rates); use metrics to drive continuous improvement.
Evaluate and introduce technologies that improve performance and developer productivity.
What we’re looking for
10+ years software engineering experience; 5+ years in engineering management or equivalent.
Strong Java (Java 8+) expertise and proven experience building production microservices.
Experience with Spring Boot, Spring Cloud, messaging (Kafka/RabbitMQ), and databases (Oracle, Postgres, Redis, etc.).
Cloud & container experience (AWS/Azure/GCP, Kubernetes/Docker).
Hands-on with CI/CD, IaC (Terraform/CloudFormation), and observability tools (Prometheus/Grafana/ELK).
Solid knowledge of secure development practices and payment industry/regulatory requirements.
Familiarity with specification-driven AI development, including structured workflows, schema-based outputs, guardrails, and evaluation-driven AI system design.
Familiarity with ML frameworks and tooling (TensorFlow, PyTorch, scikit-learn), model orchestration (Kubeflow, MLflow), and cloud AI services (SageMaker, Vertex AI, Azure ML); or demonstrated ability to evaluate and adopt equivalent solutions.
Demonstrated ability to lead through ambiguity, manage complex stakeholder networks, and deliver under high operational pressure.
Excellent communicator and stakeholder partner; experience in fintech/payments preferred.