Overview
Skills
Job Details
Job Role: AI/ML Engineer
Location: Remote
Duration: 12+ Months Contract on W2
Role Description:
We are looking for an AI Engineer with strong experience in Amazon Bedrock, AWS platform services, agentic AI patterns, and Python to design, build, and operationalize GenAI solutions. You will work closely with product owners, architects, and business stakeholders to turn use cases into robust, secure, and scalable AI applications on AWS.
Key Responsibilities
· Solution Design & Development
o Design and implement GenAI solutions using Amazon Bedrock (e.g., model selection, prompt orchestration, guardrails, evaluation).
o Build agentic AI systems (tool-using agents, multi-step workflows, RAG pipelines, planners/executors) in Python.
o Develop APIs, microservices, and backend components in Python to integrate AI capabilities into applications.
o Implement retrieval pipelines (RAG) using AWS services (e.g., OpenSearch, DynamoDB, S3, Kendra, Aurora).
· AWS Platform & MLOps
o Deploy and operate AI workloads using AWS services such as Lambda, ECS/EKS, Step Functions, EventBridge, S3, CloudWatch, IAM, CloudFormation/CDK.
o Implement CI/CD for AI and data services (e.g., CodePipeline / GitHub Actions).
o Monitor performance, cost, and reliability of AI workloads, and optimize as needed.
· Data & Security
o Work with structured and unstructured data (text, documents, logs, PDFs, etc.) to power LLM-based applications.
o Ensure security, compliance, and governance for AI solutions (IAM, KMS, data masking, network security).
o Collaborate with data engineers and architects on data pipelines and data quality.
· Collaboration & Stakeholder Engagement
o Partner with product owners and business SMEs to refine use cases and success criteria.
o Create technical documentation, design diagrams, and best-practice guidelines.
o Support demos, PoCs, and pilot implementations with stakeholders and clients.
o Mentor junior engineers on AWS, Python, and AI best practices.
Required Qualifications
· Bachelor’s degree in Computer Science, Engineering, or related field; or equivalent practical experience.
· 3–7+ years of experience in software engineering / data engineering / ML engineering (adjust years as needed).
· Strong proficiency in Python, including experience building APIs, services, or automation.
· Hands-on experience with Amazon Bedrock (model configuration, inference, prompt management, evaluation).
· Experience designing and implementing agentic AI applications (e.g., tool-calling agents, workflow orchestration, multi-agent systems).
· Practical experience with core AWS services:
o Compute: Lambda, ECS/EKS, or EC2
o Storage & Data: S3, DynamoDB / RDS / Aurora
o Integration: API Gateway, Step Functions, EventBridge/SQS
o Security & Ops: IAM, CloudWatch, CloudTrail
· Experience with Git and modern CI/CD practices.
· Strong understanding of software engineering fundamentals (testing, logging, error handling, performance).