Hybrid Data Scientist: AWS ML/LLM & Agentic AI Engineer

Apexon; Auburn Hills (MI); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health Insurance with Dental & Vision

401K Plan

Life Insurance, STD & LTD

Paid Vacations & Holidays

Paid Parental Leave

FSA Dependent & Limited Purpose care

Job summary

Apexon is seeking a highly technical Data Scientist in Auburn Hills, MI (Hybrid) to design, build, and operationalize ML/AI solutions on AWS with a strong emphasis on governance, security, and tooling. You will deliver LLM-based models, agentic AI systems, and RAG architectures while ensuring scalable deployment and monitoring across the full model lifecycle.

Strong coding in Python/Java, experience with Docker/Kubernetes, and front-end interfaces (React/TypeScript) are required to surface model

Qualifications

• Strong hands-on experience building and deploying ML solutions on AWS.
• Proven experience with LLMs, including OpenAI models/APIs, and current knowledge of leading AI/LLM model families.
• Hands-on experience building agentic AI systems (multi-agent orchestration, tool use, autonomous workflows).
• Experience building RAG systems, including semantic RAG (embeddings, vector databases, semantic retrieval).
• Deep understanding of data: exploration, quality, feature engineering, and its impact on model outcomes.
• Strong coding proficiency in Python and Java.
• Experience building front-end interactive applications (React, TypeScript, or Java-based UI) to surface model outputs to end users.
• Practical experience with Docker/containers and GPU compute for training/inference.
• Experience building and maintaining CI/CD pipelines for ML/AI workloads.
• Working knowledge of DevSecOps practices applied to ML pipelines.
• Experience providing operational support for production ML/AI systems, including monitoring and incident response.
• Experience implementing model governance and monitoring (drift detection, performance tracking, periodic retraining/tuning cycles).
• Demonstrated ability to design for human-in-the-loop / human-on-the-loop workflows for model oversight, retraining, and tuning.
• Demonstrated judgment in model/technique selection, including when to use AI/LLM approaches vs. traditional methods.
• Experience defining measurable testing/evaluation criteria for model performance and quality.
• Experience writing automated test cases, including using AI-assisted approaches to generate test coverage for model builds.
• Solid understanding of AI governance, legal, and security requirements, and experience embedding guardrails into model development.
• Familiarity with ML/AI frameworks (e.g., PyTorch, TensorFlow, Hugging Face, LangChain/LlamaIndex or similar agentic/RAG frameworks).

Responsibilities

• Design, build, train, and validate machine learning models on AWS with strong feature engineering.
• Develop solutions using LLMs and generative AI, including OpenAI modules/APIs.
• Design and implement agentic AI solutions (multi-step, tool-using, autonomous workflows).
• Build and evaluate RAG solutions with embeddings and vector search.
• Apply appropriate model types and architectures for each problem.
• Design for HITL/HOTL patterns and governance in inference and retraining workflows.
• Establish measurable testing and evaluation criteria for model performance.
• Write and maintain automated test cases for model validation and expand test coverage.
• Provide operational support for deployed models, including monitoring and incident triage.
• Implement governance and monitoring frameworks to track drift, bias, and usage over time.
• Own the model update lifecycle: retraining, fine-tuning, versioning, re-validation.
• Use logging and audit trails to track decisions and lineage over time.
• Build and deploy models on AWS and containerized pipelines; CI/CD for ML workloads.
• Apply DevSecOps principles across the ML lifecycle and ensure security compliance.
• Maintain awareness of governance, security, and regulatory requirements in AI development.

Skills

AWS

LLMs

Agentic AI

RAG

Python

Java

React

TypeScript

Docker

CI/CD

DevSecOps

MLOps

Monitoring

Governance

Security

Tools

OpenAI APIs

AWS SageMaker

Docker

Kubernetes

React

TypeScript

Python

Java

LangChain

Job description

Apexon is seeking a highly technical Data Scientist in Auburn Hills, MI (Hybrid) to design, build, and operationalize ML/AI solutions on AWS with a strong emphasis on governance, security, and tooling. You will deliver LLM-based models, agentic AI systems, and RAG architectures while ensuring scalable deployment and monitoring across the full model lifecycle.

Strong coding in Python/Java, experience with Docker/Kubernetes, and front-end interfaces (React/TypeScript) are required to surface model