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# AI/ML Engineer

- **Company:** Oms Medical Billing Llc
- **Location:** Addison, TX, United States
- **Experience:** Expert
- **Salary:** $115,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Data Cleansing, Python (Programming Language), Large Language Models, Multi-Agent Systems, Prompt Engineering, IT Architecture, Build Management, Kubernetes, Machine Learning Operations
- **Published:** July 11, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b36b63b6eaa96793

## About the Role

* 6+ years of Python engineering; 3+ years building production ML or LLM systems
 * Deep hands-on experience with at least one major LLM provider (Azure OpenAI, Anthropic, AWS Bedrock) and frameworks such as LangChain, LlamaIndex, LangGraph, or equivalent
 * Strong foundation in ML evaluation, prompt engineering, RAG, fine-tuning, and model observability
 * Experience deploying models on cloud infrastructure; MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar)
 * Healthcare or regulated-industry experience strongly preferred; familiarity with HIPAA technical safeguards required
 * Pragmatic engineer who can scope, ship, and measure - not a research-only profile

## Description

We are seeking a hands-on AI/ML Engineer to define how AI is built, evaluated, and operated across our portfolio. You will own the technical depth of our AI capability - LLM applications, classical ML, and emerging agentic patterns - in production, at scale, in a regulated environment.

This is a senior IC role for an engineer who wants to build, not just advise.

What You'll Do

 * Design and build production AI/ML systems - LLM applications, classical ML, and emerging agentic patterns
 * Own the full lifecycle: data preparation, model selection, fine-tuning/prompt engineering, evaluation, deployment, and monitoring
 * Build evaluation frameworks and safety guardrails for LLM-based systems handling sensitive data
 * Partner with Data, Engineering, and Security teams to architect AI workloads that meet HIPAA and SOC 2 standards
 * Productionize models - APIs, pipelines, observability, drift detection, retraining loops
 * Contribute to our AI architecture and platform decisions: model gateways, vector stores, RAG patterns, agent frameworks


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