AI Engineer

SFE; Malvern (Chester County); Ibrido; USD 120.000 - 150.000; Tempo pieno

Descrizione del lavoro

SFE is seeking an experienced AI/ML engineer to design, develop, and deploy Generative AI and ML solutions on AWS Bedrock and SageMaker. The role focuses on building robust RAG pipelines, AI agents, and scalable ML operations within a hybrid work model in the United States.

You will collaborate with business, data engineering, and cloud teams to deliver production-ready AI solutions with strong governance, cost awareness, and performance optimization.

Competenze

• Experience designing and deploying Generative AI and ML solutions on AWS.
• Proficiency with Python, PySpark, SQL, and NLP.
• Hands-on with LLMs, RAG, and AI agents.
• Familiarity with LangChain, LangGraph, and LlamaIndex.
• Experience with Terraform, Docker, Kubernetes, and CI/CD pipelines.

Mansioni

• Design, develop, and deploy AI/ML and Generative AI solutions on AWS Bedrock, SageMaker, Lambda, and S3.
• Build and optimize RAG pipelines, LLM-based apps, AI agents, and model inference workflows.
• Develop scalable data pipelines and MLOps frameworks for training, deployment, monitoring.
• Collaborate with business, data engineering, and cloud teams to deliver secure, production-ready AI solutions with governance and cost optimization.

Conoscenze

Generative AI

LLMs

NLP

Machine Learning

Deep Learning

Prompt Engineering

RAG

AI Agents

LangChain

LlamaIndex

Strumenti

AWS Bedrock

AWS SageMaker

Python

PySpark

SQL

S3

Lambda

IAM

RDS

CloudWatch

MLOps

MLflow

CI/CD Pipelines

Docker

Kubernetes

Terraform

REST APIs

FastAPI

Descrizione del lavoro

Must Have Technical/Functional Skills

• Strong experience in designing, developing, and deploying Generative AI and Machine Learning solutions on
• AWS using Bedrock, SageMaker, Python, MLOps, and cloud-native architecture
• Python, PySpark, SQL
• Machine Learning, Deep Learning, NLP
• Generative AI, LLMs, Prompt Engineering
• Amazon Bedrock, AWS SageMaker
• RAG (Retrieval Augmented Generation), AI Agents
• LangChain, LangGraph, LlamaIndex
• AWS Services: S3, Lambda, IAM, RDS, CloudWatch
• MLOps, MLflow, CI/CD Pipelines
• Docker, Kubernetes, Terraform
• REST APIs, FastAPI, Model Deployment & Monitoring

Roles & 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.

Generic Managerial Skills, If any

• Strong leadership and stakeholder management skills, with experience leading cross-functional teams and driving delivery excellence.
• Effective communication with business and technical stakeholders