Technical Architect - ML - GenAI

## Technical Architect - ML
- GenAIApplylocations:
USA
- Remote time type:
Full time posted on:
Posted Yesterday time left to apply:
End Date:
September 5, 2026 (30 days left to apply) job requisition :
JR11588

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 technical leadership and mentor team members while remaining hands-on
****** Must have:****
* ** 8+ years of relevant hands-on technical experience implementing, and developing cloud ML solutions on AWS.**
* ** Hands-on experience on AWS services. Proven experience using AWS Sagemaker and Bedrock leveraging different types of data sources, Training jobs, real-time and batch applications.**
* ** Design and implement agentic AI architectures using frameworks such as Lang Chain, Strand Agents etc., enabling autonomous task planning, decision-making, and multi-step reasoning.**
* ** Hands-on experience with Amazon Agent Core for building, deploying, and scaling production-grade agentic AI applications, including agent memory management, tool registry, and observability.**
* ** Architect and deploy scalable AI solutions on AWS, leveraging services like Lambda, Bedrock, Step Functions, S3, API Gateway, and Sage Maker.**
* ** Proficiency in working with LLM APIs (e.g., Claude, Nova, and other third-party LLM providers), including API integration,and multi-model orchestration strategies.**
* ** Hands-on experience fine-tuning or optimizing large language models (LLM)**
* ** Familiarity with LLM tool use, prompt templating and context management.**
* ** Strong expertise in Vector Databases, including indexing strategies, embedding generation, similarity search, and integration with RAG architectures.**
* ** Model Evaluation & Optimization:
Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration.**
* ** Develop and maintain Model Context Protocol (MCP) implementations to manage state, context windows, memory, and prompt orchestration across distributed agent systems.**
* ** Experience with at least one of the workflow orchestration tools, Airflow, Step Functions, Sage Maker Pipelines, Kubeflow etc.**
* ** Experience implementing secure, scalable APIs and integrating with 3rd-party data sources and tools**
* ** Ability to collaborate with cross-functional teams such as Developers, QA, Project Managers, and other stakeholders to understand their requirements and implement solutions.**
* ** Should have experience with Deep Learning Concepts - Transformers, BERT, Attention models, tokenization, embeddings.
****** Nice to have:****
* ** Experience with software development, exposure to frontend backend frameworks and communication protocols**
* ** Experience working on Infrastructure as Code (IaC) and CI/CD pipelines**
* ** Experience with NLP concepts: syntactic/semantic analysis, NER etc.
*** If you like wild growth and working with happy, enthusiastic…