Request ID: 109910-1 Title: AWS GenAI Lead Engineer Locations: Malvern, PA /Charlotte, NC Duration: 6 Months Pay Range: $50 - $60/Hour on W2/C2C (All inclusive)
Introduction
We are seeking a highly skilled AWS GenAI Lead Engineer to analyze business requirements and processes, design intelligent agent workflows, and deliver secure, scalable, enterprise-grade agentic applications. The role combines hands-on engineering with technical leadership across the AWS AI ecosystem.
Required Skills & Qualifications
8 years of software engineering experience, including strong hands-on development with Python and AWS cloud-native application patterns.
2 years of AI/ML or Generative AI engineering experience, with production implementation of LLM-powered applications or autonomous agents.
Hands-on expertise with AWS Bedrock, foundation-model integration, Bedrock Agents or Knowledge Bases, and relevant AWS serverless or container services.
Practical experience with Strands Framework and at least one agent orchestration framework such as LangChain or LangGraph.
Strong FastAPI, REST API, asynchronous programming, authentication, integration, and microservices development capabilities.
Experience with RAG, prompt engineering, vector databases, embeddings, semantic search, agent tools, memory, and multi-step workflows.
Knowledge of Docker, CI/CD, infrastructure as code, logging, monitoring, testing, and secure production deployment practices.
Excellent stakeholder communication, requirements analysis, solution consulting, technical leadership, and team mentoring skills.
AWS certification in Solutions Architecture, Machine Learning, AI, or a related discipline is preferred.
Prior work experience at client or in client's Industry.
Applicants must be able to work directly for Artech on W2.
Preferred Skills & Qualifications
Experience in the BFSI industry.
Additional AWS certifications.
Experience with observability and testing in production environments.
Day-to-Day Responsibilities
Analyze business requirements and design intelligent agent workflows.