AWS Generative AI Engineer

Job Overview:

Pay Range $45hr - $50hr

Requirement/Must Have:

• Strong experience with AWS Cloud Services.
• Hands-on experience with Amazon Bedrock, AWS Lambda, API Gateway, Amazon S3, Amazon DynamoDB, Amazon OpenSearch, ECS, EKS, CloudWatch, and IAM.
• Strong experience with Amazon Bedrock and Anthropic Claude models.
• Solid understanding of Large Language Models (LLMs), prompt engineering, RAG architecture, vector databases, AI agents and agentic workflows, finetuning and model evaluation, responsible AI, and AI governance.
• Proficiency in Python.
• Experience with LangChain, LangGraph, LlamaIndex, FastAPI, REST APIs, and SDK integrations.
• Experience integrating structured and unstructured data sources.
• Knowledge of embeddings, semantic search, knowledge bases, and document ingestion pipelines.

Responsibilities:

• Design, develop, and deploy Generative AI solutions leveraging Amazon Bedrock, Anthropic Claude, and other foundation models.
• Build and optimize RAG (Retrieval-Augmented Generation) architectures using vector databases and enterprise knowledge sources.
• Develop AI-powered applications such as chatbots, virtual assistants, document processing, content generation, and intelligent search solutions.
• Create and optimize prompts, workflows, and model configurations to improve response quality, accuracy, and performance.
• Integrate Bedrock foundation models with enterprise applications, APIs, and AWS services.
• Implement scalable and secure cloud-native solutions using AWS services such as Lambda, API Gateway, ECS, EKS, S3, DynamoDB, and OpenSearch.
• Finetune model outputs through prompt engineering, guardrails, and evaluation frameworks.
• Collaborate with data engineers, architects, product owners, and business stakeholders to identify GenAI use cases and deliver solutions.
• Monitor model performance, costs, latency, and security compliance.
• Ensure adherence to responsible AI practices, governance, and security standards.
• Stay updated with emerging trends in Generative AI, LLMs, and AWS AI/ML services.

Nice to Have:

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• AWS certifications such as AWS Certified, AWS Certified Machine Learning Engineer, or AWS AI Practitioner.
• Experience with MLOps, CI/CD, and infrastructure-as-code tools like Terraform and CloudFormation.
• Familiarity with other LLM providers such as OpenAI, Meta, Llama, Mistral, or Cohere.

Skills:

• Solution Design and Architecture.
• Generative AI and LLM Expertise.
• Cloud-Native Development.
• Problem Solving and Analytical Thinking.
• Stakeholder Management.
• Innovation Mindset.
• Agile Delivery.
• Communication and Collaboration Skills.

Education and Experience:

• 5+ years of overall software/cloud development experience.
• 2+ years of hands-on experience in Generative AI and LLM-based solution development.
• Proven experience delivering enterprise-scale AI solutions on AWS.

 

Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws.

About Cynet Systems

Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia.

As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.