Generative AI Engineer (AWS Bedrock & LangChain)-5

Job Type: Contract

Job Category: IT

Job Description

Role: AWS AI Bedrock Developer

Location: Charlotte, NC (100% Onsite)

Long Term Contract – W2 / C2C

Client is seeking a highly skilled AI Agent Developer to design, build, and deploy intelligent autonomous agents using cutting-edge frameworks and generative AI platforms. This role requires deep expertise in prompt engineering, agent orchestration, and working with AWS-native services, particularly Amazon Bedrock.

Core Competencies

AWS Cloud Computing

Artificial Intelligence / Generative AI

Key Responsibilities

Autonomous Agent Development

Design, develop, and deploy multi-step, multi-tool AI agents capable of reasoning, decision-making, and task execution.

Leverage frameworks like Lang-Chain, Semantic Kernel, or custom-built orchestration layers to power agent behavior.

Prompt Engineering

Craft, refine, and optimize advanced prompts to improve LLM accuracy, reliability, and contextual performance.

Develop and manage prompt chains, system prompts, and dynamic context strategies to enable adaptive agent responses.

Continuously test and iterate prompts based on performance metrics and user feedback.

Amazon Bedrock Development

Implement generative AI solutions using Amazon Bedrock with models from providers such as Anthropic (Claude), Cohere, Stability AI, and Amazon Titan.

Utilize Bedrock capabilities including Guardrails, Knowledge Bases, and model customization to ensure safe and scalable AI deployments.

Essential Skills

Overall IT Experience: 9-12+ Years

Proven experience developing autonomous AI agents using LangChain, Semantic Kernel, or similar frameworks

Expertise in prompt engineering, including design, chaining, and iterative refinement for large language models (LLMs)

Hands-on experience with Amazon Bedrock (model integration, guardrails, knowledge bases)

Proficiency in Python, API integration, and vector databases such as FAISS or Pinecone

Strong understanding of LLM behavior, Retrieval-Augmented Generation (RAG) architecture, and AWS deployment best practices

Desirable Skills

Advanced knowledge of AI agent orchestration frameworks

Experience fine-tuning or customizing foundational models

Familiarity with prompt evaluation tools and automated testing for LLMs

Exposure to real-world AI use cases in enterprise-scale environments

Hashtags

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