Agentic AI Platform Engineer on AWS

Phase2 Technology; San Antonio (TX); Hybrid; USD 99,000 - 225,000; Full time

Benefits offered by this job

Health benefits

Paid leave

Tuition assistance

Professional development

Work-life programs

Job summary

Phase2 Technology is seeking an experienced AI/ML engineer to design, train, and deploy agentic AI and retrieval-augmented systems on AWS, collaborating across data, software, and DevSecOps teams to deliver secure capabilities.

You will own mission-critical solutions, applying best-fit ML algorithms and deployment patterns while ensuring traceable outputs and scalable performance for national security contexts.

Qualifications

• Experience building AI/ML applications including agentic AI and retrieval augmented systems.
• Ability to design, train, test, deploy and maintain models on AWS.
• Familiarity with DevSecOps, CI/CD, testing, and infrastructure as code.

Responsibilities

• Train, test, deploy and maintain AI/ML models and agentic applications.
• Collaborate with data engineers, data scientists, software engineers and DevSecOps.
• Deliver secure AWS-based capabilities processing structured and unstructured data.
• Support human decision-making with traceable outputs.

Skills

AI/ML engineering

Data science

Software engineering

Data engineering

Cloud engineering

Python

APIs integration

DevSecOps practices

Version control

CI/CD

Containerization

Infrastructure as code

Education

Bachelor's degree

Tools

LangChain

LangGraph

LlamaIndex

Bedrock

SageMaker

OpenSearch

Knowledge Bases

Bedrock Guardrails

Retrieval-augmented

Embeddings

Vector search

Temporal

EventBridge

AWS CDK

Terraform

CloudFormation

Docker

Kubernetes

EKS

ECS

CI/CD

FastAPI

Pydantic

OpenAPI

Job description

Phase2 Technology is seeking an experienced AI/ML engineer to design, train, and deploy agentic AI and retrieval-augmented systems on AWS, collaborating across data, software, and DevSecOps teams to deliver secure capabilities.

You will own mission-critical solutions, applying best-fit ML algorithms and deployment patterns while ensuring traceable outputs and scalable performance for national security contexts.