Test Engineer | Machine Learning | Azure ML

Company

Description:

IMCS Group is one of the fastest growing MWBE (Minority Woman Owned Enterprise) staffing firms in the U.S. We focus on bringing a Diversity Recruitment approach to Fortune 500 companies within North America and EMEA region contingent labor programs. IMCS Group excels in providing top talent in IT, Healthcare, Engineering, Finance, Light Industrial, Contact Center, and Clerical. We have offices in the US, Canada, Mexico, and India in which we can provide support to our clients.

Description:

POC:
Sam Chavez

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Job Title:

Test Engineer | Machine Learning | Azure ML - Software Engineer
Work Location & Reporting Address:
Fort Worth, TX 76155 (Onsite. Candidate will be working hybrid; onsite 3 days a week and 2 days virtually)
Contract duration: 6
MAX VENDOR RATE:
*** per hour max
Target

Start Date:

05 May 2026
Does this position require Visa independent candidates only? No

Must Have

Skills:

5+ years software engineering experience with strong proficiency in Python, plus working knowledge of at least one of Java, Go, or Type Script; 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, Cloud Formation, or Pulumi).

Working experience with LLM integration patterns, prompt engineering, or AI/ML application development; familiarity with frameworks like Lang Chain, Lang Graph, or similar orchestration tools.

Nice to Have

Skills:

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

Detailed

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.
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.
Candidate will be working hybrid; onsite 3 days a week and 2 days virtually. Interviews will have 2 rounds
Top 3 Mandatory

Skills and Experience:

1) 5+ years software engineering experience with strong proficiency in Python, plus working knowledge of at least one of Java, Go, or Type Script; 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, Cloud Formation, or Pulumi).
3)

Working experience with LLM integration patterns, prompt engineering, or AI/ML application development; familiarity with frameworks like Lang Chain, Lang Graph, or similar orchestration tools.
Nice to Have

Skills:

Experience with event-driven architectures (Kafka, Event Bridge), vector databases, observability tools (Datadog, Splunk, Open Telemetry), agent evaluation frameworks,…