USA_Engineer

Pay Rate Range

$ 49.24 - 53.03/hr.

Role Title

AWS Bedrock

Job Description

• Develop, integrate, and optimize Generative AI applications using AWS Bedrock, including prompt engineering, RAG implementation, and AI agent workflows.
• Create and optimize prompts for LLMs
• Work with Amazon Bedrock APIs for model inference
• Develop backend services using Python / Node.js
• Enable real-time and streaming AI responses
• Build AI solutions using Bedrock Knowledge Bases
• Integrate with data sources (S3, databases, enterprise systems)
• Implement vector search and embeddings
• Design and build AI agents using Bedrock Agents
• Implement multi-step workflows and task automation
• Integrate external APIs/tools into AI workflows

Work with core AWS services

o IAM (security & access control) o S3 (data storage) o Lambda (serverless compute) o API Gateway (service exposure)

• Deploy scalable and secure AI solutions
• Implement guardrails and content filtering
• Ensure data privacy, compliance, and safe AI usage
• Optimize token usage and model selection
• Monitor and control Bedrock usage costs
• Convert business requirements into AI-driven solutions
• Manage and utilize SageMaker Feature Store for reusable feature engineering
• Monitor model performance and detect data drift in production systems
• Maintain and retrain models for continuous performance improvement
• Track experiments, metrics, and ensure model reproducibility
• Integrate SageMaker with AWS services like S3, IAM, Lambda, and CloudWatch
• Optimize infrastructure, performance, and cost of ML workloads
• Collaborate with cross-functional teams to design and deliver ML solutions

Must Have Technical/Functional Skills

Generative AI & LLM Fundamentals, Prompt Engineering, Bedrock API and SKD usage, RAG, AI Agents and workflow design, Programming skill (Python, APIs, Microservice), AWS core knowledge (IAM, S3, Lambda, API Gateway), Application integration skills, Vector databases, CI/CD for AI Apps.

Understanding of ML life cycle, Strong coding in Python, Good knowledge on Py libraries (Pandas, Numpy, Scikit-learn (ML), Tensorflow/PyTorch), Exploratory Data Analysis (EDA), Handling large dataset in Amazon S3, Model Training and Optimization, Model deployment, MLOps & Pipeline Automation.

Hands on SageMaker Studio, Training Jobs, Endpoints, Pipeline, Model registry, Feature Store Hands on AWS Core services (S3, IAM, EC2, Lambda, Cluodwatch)

Generic Managerial Skills, If any

• Leadership skills, People management, Analytical skills
• Excellent communication and collaboration skills, risk management
• Should work with CXO, infrastructure, security, development teams.

We are looking for a AWS Bedrock Engineer with deep expertise in AWS| DevOps| andDevSecOps practices| who can design and maintain secure| scalable| and developer-friendlyplatforms. This role will champion developer experience by building self-service capabilities|golden paths| and automation for common workflows| while ensuring platform reliability throughSRE practices and compliance automation. The ideal candidate will have experience with Atlassian Compass (preferred) or Backstage for Internal Developer Portals| strong CICD skills|and a solution-oriented mindset. Previous development experience is a plus

Skills

Digital

Amazon Web Service(AWS) Cloud Computing~Digital

DevOps~Github Enterprise

Experience Required

10 & Above

Skills

Category

Name

Required

Importance

Experience

SkillCategoryTest1_MN

Digital

Amazon Web Service(AWS) Cloud Computing

Yes

1

>7 years