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Gen AI Tech Lead (Generative AI & Agentic Systems) at Remote, Remote, USA
Email: [email protected]
http://bit.ly/4ey8w48
https://jobs.nvoids.com/job_details.jsp?id=3201357&uid=a6997793f7df48d9b553ae9b915545ad

From:

Raj Methre,

Centraprise

[email protected]

Reply to: [email protected]

Hi Team,

Greetings from Centraprise,

Job Role- Gen AI Tech Lead (Generative AI & Agentic Systems)

Location:

New Jersey (Hybrid)

Experience Level:

Senior (13+ 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, Lang Graph, 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.

Note

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Thanks & Regards

Raj Methre

Sr Acquisition Specialist

Centraprise corp,

[email protected]

Desk: +

1 732-476-5515 *(1025)

linkedin.com/in/raj-b-methre-720b55223

Keywords: continuous integration continuous deployment artificial intelligence javascript sthree information technology Idaho
Gen AI Tech Lead (Generative AI & Agentic Systems)
[email protected]
http://bit.ly/4ey8w48
https://jobs.nvoids.com/job_details.jsp?id=3201357&uid=a6997793f7df48d9b553ae9b915545ad
[email protected]
View All
06:59 PM 11-Mar-26


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