Technical Architect - ML - GenAI
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It closed on 9/6/2026. The full description is kept below for reference. You can express your interest directly via ResumeKart below to be placed in our priority candidate showcase for recruiters hiring for similar roles.
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Job Description
While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi ! Role: Gen AI Architect (AWS) Experience Level: 8+ Years Work location: Remote (US)
Job Overview
We are looking for a Generative AI Architect / Lead to design and deliver enterprise-grade GenAI solutions using AWS Bedrock and Agentcore. This role focuses on building scalable applications leveraging large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI workflows.
The ideal candidate will be a hands-on architect who can define solution architecture, guide teams, and actively contribute to development while ensuring performance, scalability, and cost efficiency.
Key Responsibilities
Design and implement GenAI solutions using AWS Bedrock and Agentcore Define architecture for LLM-based applications, including RAG pipelines and agentic workflows Develop and orchestrate agentic AI workflows, enabling multi-step reasoning, tool usage, and task automation Build and manage RAG pipelines, including embeddings, retrieval mechanisms, and vector databases Integrate LLM capabilities into enterprise applications via APIs and backend services Design and optimize prompt engineering strategies for accuracy, relevance, and performance Work with structured and unstructured data sources to enable knowledge-driven AI applications Ensure model evaluation, monitoring, and optimization for latency, cost, and response quality Collaborate with application, data, and platform teams for end-to-end solution delivery Define best practices for security, governance, and responsible AI usage Troubleshoot and resolve issues in production GenAI systems Provide techni
Required Skills
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