AI AWS Bedrock Engineer

Xforia Global Talent & Technology Solutions; Marysville (OH); On-site; USD 120,000 - 160,000; Full time

Job summary

Xforia Global Talent & Technology Solutions is seeking a skilled AI/ML engineer to design and implement LLM-based applications and RAG pipelines. You will architect agentic workflows, fine-tune prompts, and ensure scalable, secure AI services across the stack.

Responsibilities include integrating foundation models via AWS Bedrock, building vector search and retrieval pipelines with OpenSearch, Pinecone, or similar DBs, and deploying robust APIs using Python (FastAPI/Flask) or Node.js.

Qualifications

• Experience designing and implementing LLM-based applications.
• Experience with AWS Bedrock and AWS AI services.
• Experience building retrieval and vector-search pipelines with OpenSearch/OpenSearch-compatible or Pinecone-like systems.

Responsibilities

• Design and implement LLM-based applications and RAG pipelines.
• Integrate foundation models via AWS Bedrock and manage model guardrails.
• Build and optimize vector search and retrieval pipelines (OpenSearch, Kendra, Pinecone).
• Implement agent orchestration frameworks for multistep reasoning tasks.
• Build scalable APIs and microservices using Python (FastAPI/Flask) or Node.js.

Skills

ASP.NET MVC

Prompt Engineering

Python

API design

Tools

AWS Bedrock

AWS AI Services

OpenSearch

Kendra

Pinecone

LangChain

LangGraph

Bedrock Agents

FastAPI

Flask

EC2

EKS

SageMaker

API Gateway

Lambda

S3

DynamoDB

RDS

Aurora

Job description

Design and implement LLMbased applications RAG pipelines agentic workflows finetuning prompt engineering

Integrate foundation models via Amazon Bedrock and manage model selection guardrails and evaluation

Build and optimize vector search and retrieval pipelines Amazon OpenSearch Kendra or thirdparty vector DBs like Pinecone on AWS

Implement agent orchestration frameworks LangChain LangGraph Bedrock Agents for multistep reasoning tasks

Build scalable APIs and microservices using Python FastAPIFlask or Nodejs

Implement data pipelines with AWS Glue EMR or native Python ETL for traininginference data prep

Manage containerized workloads via ECSEKS

Build responsive UIs that consume backend AI services

Implement realtime streaming responses for chatstyle AI interfaces

Integrate authentication Amazon Cognito and rolebased access control

Architect solutions using core AWS services Bedrock SageMaker Lambda API Gateway S3 DynamoDB RDSAurora ECSEKS Step Functions

Set up CICD pipelines CodePipeline CodeBuild or GitHub Actions AWS deploy

Manage cost optimization for AI workloads token usage monitoring model routing caching strategies via ElastiCache

Mandatory Skills

ASP.NET MVC, AWS AI Services, AWS Bedrock, Prompt Engineering