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# Software Engineer(Full Stack Python)

- **Company:** Dolphin Solutions Inc
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Python (Programming Language), Redis, Software Engineering, Systems Integration, TypeScript, Workflow Management Systems, Datadog, Data Logging, Pulumi, Flask (Web Framework), Large Language Models, Grafana, Prompt Engineering, Caching, Cloudformation, Fastapi, Event Driven Architecture, Containerization, AI Platforms, Kubernetes, Deployment Automation, Apache Kafka, Api Design, Terraform, Splunk, Grpc, Docker, Microservices
- **Published:** June 1, 2026
- **Apply:** https://www.dice.com/job-detail/b4dadd75-e60b-4e3a-a2b0-64dab2654be3

## About the Role

* 5+ years software engineering experience with strong proficiency in Python, plus working knowledge of at least one of Java, Go, or TypeScript; hands-on experience building production REST/gRPC APIs and microservices.
 * Solid experience with cloud platforms (AWS or Azure preferred), containerization (Docker/Kubernetes), CI/CD pipelines, and infrastructure-as-code (Terraform, CloudFormation, or Pulumi).
 * Working experience with LLM integration patterns, prompt engineering, or AI/ML application development; familiarity with frameworks like LangChain, LangGraph, or similar orchestration tools.

Nice to Have Skills:

 * Experience with event-driven architectures (Kafka, EventBridge), vector databases, observability tools (Datadog, Splunk, OpenTelemetry), agent evaluation frameworks, FastAPI/Flask, async Python, Redis/caching patterns, airline or travel industry experience.

## Description

As a Software Engineer on the Agentic System Layer (ASL) team, you will build and maintain the core platform components that power American Airlines' agentic AI systems. Day-to-day responsibilities include: developing and maintaining agent orchestration services, tool registries, and execution runtimes; building APIs and microservices for LLM integration, prompt management, and agent lifecycle management; implementing observability, logging, and monitoring for agentic workflows; writing comprehensive tests (unit, integration, end-to-end) for platform reliability; collaborating with architects on design decisions and with ML engineers on model integration; participating in on-call rotations for production support of the AI platform; contributing to CI/CD pipelines, infrastructure-as-code, and deployment automation.


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