Generative AI & ML Engineer - AWS SageMaker & Bedrock

SFE; Malvern (Chester County); On-site; USD 120,000 - 160,000; Full time

Job summary

SFE is seeking an AI ML Engineer in Malvern, PA to design, develop, and deploy Generative AI and ML solutions on AWS. You will build scalable data pipelines, RAG workflows, and AI agents, while collaborating with cross-functional teams to ensure secure, production-ready implementations.

Responsibilities include deploying models, optimizing pipelines, and maintaining governance and cost controls. Strong Python, PySpark, and SQL skills are required, with experience in CI/CD and cloud-native

Qualifications

• Strong experience in designing, developing, and deploying Generative AI and Machine Learning solutions on AWS using Bedrock, SageMaker, Python, MLOps, and cloud-native architecture.
• Proficient in Python, PySpark, SQL for data processing and model workflows.
• Experience with ML lifecycle, model deployment, monitoring, and governance.

Responsibilities

• Design, develop, and deploy AI/ML and Generative AI solutions using AWS services such as Bedrock, SageMaker, Lambda, and S3.
• Build and optimize RAG pipelines, LLM-based applications, AI agents, and model inference workflows to solve business problems.
• Develop scalable data pipelines and MLOps frameworks for model training, deployment, monitoring, and continuous improvement.
• Collaborate with business, data engineering, and cloud teams to deliver secure, production-ready AI solutions while ensuring performance, governance, and cost optimization.

Skills

Generative AI

LLMs

Prompt Engineering

NLP

Python

PySpark

SQL

MLOps

CI/CD pipelines

Tools

AWS Bedrock

AWS SageMaker

LangChain

LangGraph

LlamaIndex

Terraform

Docker

Kubernetes

REST APIs

FastAPI

Job description

SFE is seeking an AI ML Engineer in Malvern, PA to design, develop, and deploy Generative AI and ML solutions on AWS. You will build scalable data pipelines, RAG workflows, and AI agents, while collaborating with cross-functional teams to ensure secure, production-ready implementations.

Responsibilities include deploying models, optimizing pipelines, and maintaining governance and cost controls. Strong Python, PySpark, and SQL skills are required, with experience in CI/CD and cloud-native