Lead Full-Stack Engineer - Temporal Orchestrator (Remote)

Humana Inc

Honolulu (HI)

Hybrid

USD 129,000 - 178,000

Full time

9 days ago

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Job summary

Humana Inc. is seeking a Lead Full Stack Engineer to own the NBA platform’s orchestration and state machine, built in Node.js/TypeScript on Temporal.

You will lead a small team, ensure durable workflow execution, and drive reliable action delivery across member journeys and channels. Responsibilities include designing durable workflows, implementing Transactional Outbox patterns, activating decisions to Adobe Experience Platform, and coordinating with platform teams.

Qualifications

Bachelor's degree in computer science or relevant area.
6+ years of full stack software engineering experience, with 1–2 years in tech-lead capacity.
Strong Node.js/TypeScript backend experience building production services.
Hands-on experience with workflow orchestration platforms, Temporal preferred (or Cadence/Step Functions/Airflow).
Strong distributed systems fundamentals: event-driven architectures, retries, idempotency, failure recovery.
Experience designing Kafka producer/consumer patterns in production.
Experience building reliable event delivery systems using Transactional Outbox or similar patterns.
Demonstrated ability to lead a small pod through delivery and be accountable for outcomes.
Experience operating cloud-native systems on Azure or similar, using Kubernetes/containers/CI/CD.
Clear communicator to represent pod architecture and delivery status to stakeholders.

Responsibilities

Pod delivery — end-to-end delivery for orchestration pod.
Workflow orchestration — durable, long-running workflows on Temporal in Node.js/TypeScript.
Action delivery architecture — end-to-end delivery pipeline with Transactional Outbox patterns and idempotency controls.
Activation integrations — activate decisions to Adobe Experience Platform and publish via Kafka.
Hands-on development — contribute code for Temporal workflows, Node.js services, Kafka, and integrations.
Technical decisions — day-to-day architecture decisions for pod, including retries and schema evolution.
Distributed systems reliability — ensure exactly-once intent via idempotency and deduplication.
Observability and operations — monitoring, tracing, alerting across workflows and delivery pipelines.
Team leadership — mentor engineers, conduct code reviews, uphold standards.
Cross-team coordination — surface dependencies with decisioning, Action Library, and platform teams.