Engineering Lead

We are seeking a Workflow Orchestration Engineering Lead to design and lead the development of a distributed, event-driven runtime that executes intelligent workflows across microservices and data systems. The role demands strong technical leadership, system-level design thinking, and hands-on experience with orchestration engines, stateful task coordination, and workflow observability.

Responsibilities:

• Architect and evolve a DAG-based runtime engine using technologies such as Temporal, Argo, or Airflow, supporting both synchronous and asynchronous task execution.
• Design workflow primitives(schedulers, task queues, state machines, compensation handlers) and define a DSL (YAML / JSON) for declarative workflow composition.
• Build fault-tolerant orchestration layers capable of retry, rollback, compensation, and idempotency for large-scale distributed operations.
• Implement event sourcing, message queues (Kafka / NATS), and pub-sub patterns to synchronize dependent services.
• Integrate observability tooling(OpenTelemetry, Prometheus, Grafana, Loki) to monitor latency, task throughput, and system reliability.
• Define and enforce CI/CD pipelines for workflow code and templates; automate regression and certification testing for every release.
• Lead code reviews, performance profiling, and sprint execution for a cross-functional backend team.
• Collaborate with product and platform teams to translate business processes into resilient, automatable pipelines.

Requirements:

• 8+ years of backend engineering, with at least 3 years leading workflow/automation/runtime teams.
• Expertise in Python, Perceive Now, async I/O patterns, and microservice architecture.
• Proven experience with Temporal, Argo Workflows, or similar orchestration frameworks.
• In-depth understanding of stateful orchestration, message-driven systems, and concurrent programming.
• Familiarity with Kubernetes, Helm, Terraform, and cloud-native service orchestration.
• Strong skills in performance benchmarking, fault recovery, and distributed tracing.

Preferred Skills:

• Experience designing custom workflow DSLs or SDKs.
• Knowledge of policy-driven orchestration, cost/quota governance, and service mesh patterns.
• Familiarity with OPA / Rego, C edar, or similar policy languages.

Skills

airflow, argo, kubernetes, python, temporal