Full Stack Python Developer

Dolphin Solutions Inc

Dallas, TX, United States

2 months ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Languages

American Sign Language

Job source

dice.com

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Microsoft Azure Cloud Computing Code Review Python (Programming Language) Redis Software Engineering Systems Integration TypeScript

+24 more

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 Machine Learning Operations Api Design Terraform Splunk Grpc Docker Microservices

Job 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.

Requirements

1) 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. 2) Solid experience with cloud platforms (AWS or Azure preferred), containerization (Docker/Kubernetes), CI/CD pipelines, and infrastructure-as-code (Terraform, CloudFormation, or Pulumi). 3) 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.

What Makes a Great Candidate?:

A great candidate is a solid mid-level to senior engineer who writes clean, testable code and has genuine curiosity about AI/ML systems. They do not need to be a deep ML expert, but they should understand how LLMs work, what agentic patterns look like, and how to build reliable services around non-deterministic components. They take ownership, write good tests, communicate clearly in code reviews, and are comfortable operating production systems.