Fwd: Looking for AI Engineer (Generative AI & Agentic Systems) with AWS || New York / New Jersey (Hybrid)

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---------- Forwarded message ----------
From: Nitin <recruiternitin3112@gmail.com>
Date: 28 Jan 2026 23:19
Subject: Looking for AI Engineer (Generative AI & Agentic Systems) with AWS || New York / New Jersey (Hybrid)
To: Daily C2C Roles shashank <daily-c2c-roles-shashank@googlegroups.com>
Cc:

Hi,

Hope you are doing well.

 

Position: AI Engineer (Generative AI & Agentic Systems) with AWS

Location: New York / New Jersey (Hybrid)

Duration: Contract

Exp: 12+ years

 

Experience Level: Senior (10+ years in IT/Software, 2+ years in Generative AI, 5+ Years' in AWS)

 

Job Summary

We are looking for a highly skilled AI Engineer to lead the design and implementation of next-generation Generative AI solutions using the AWS Bedrock platform. In this role, you will be responsible for architecting robust Retrieval-Augmented Generation (RAG) pipelines and building autonomous AI Agents that can plan, reason, and execute complex business workflows.

The ideal candidate has a deep understanding of Large Language Models (LLMs), experience with vector databases, and a proven track record of deploying production-grade AI applications within the AWS ecosystem.

 

Key Responsibilities

•             Architect RAG Systems: Design and optimize end-to-end RAG workflows using Amazon Bedrock Knowledge Bases, ensuring high retrieval accuracy and minimal hallucination.

•             Develop AI Agents: Build and deploy intelligent agents using Agents for Amazon Bedrock to automate multi-step tasks, integrating them with enterprise APIs and Lambda functions.

•             Model Selection & Tuning: Evaluate and select the best foundation models (e.g., Claude 3.5, Llama 3, Amazon Titan) for specific use cases based on performance, latency, and cost.

•             Vector Database Management: Implement and manage vector stores such as Amazon OpenSearch Serverless, Pinecone, or pgvector to support semantic search capabilities.

•             Prompt Engineering: Develop and iterate on complex system prompts and advanced prompting techniques (Chain-of-Thought, ReAct) to improve agent reasoning.

•             Security & Guardrails: Implement Amazon Bedrock Guardrails to ensure responsible AI practices, including PII masking and content filtering.

•             Performance Evaluation: Use frameworks like Ragas or TruLens to systematically evaluate RAG performance (faithfulness, relevancy) and agent success rates.

Technical Qualifications

•             Programming: Expert-level proficiency in Python and experience with asynchronous programming. Familiarity with Java or Node.js is a plus.

•             AWS Ecosystem: Hands-on experience with AWS Bedrock, Lambda, S3, DynamoDB, IAM, and Step Functions.

•             AI Frameworks: Deep knowledge of orchestration frameworks like LangChain, LangGraph, or LlamaIndex.

•             Data Engineering: Experience building ETL pipelines for unstructured data (PDFs, HTML, Markdown) to feed into knowledge bases.

•             DevOps/MLOps: Proficiency in CI/CD for AI, including model versioning and monitoring using Amazon CloudWatch.

 

Preferred Skills

•             Experience with GraphRAG using Amazon Neptune.

•             Background in Banking/Financial Services or Wealth Management domains.

•             AWS Certified Machine Learning – Specialty or AWS Certified AI Practitioner.

•             Contributions to open-source AI projects.

 

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