Technical Architect – ML, GenAI

🕒 September 15

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

🔙 Backend Engineer

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👻 Ghost score 24%

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Quantiphi

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2013

💼 Consulting

🏥 Healthcare

📦 Logistics

💰 Series A on 2019-12

Consulting • Healthcare • Logistics

Quantiphi is a leading AI-first digital engineering company that leverages a decade of industry expertise to empower businesses through scalable, secure, and adaptable AI solutions. By integrating cutting-edge technology with real-world applications, Quantiphi transforms organizations across various sectors including healthcare, finance, education, and retail. Their services span AI applications, data analytics, cloud infrastructure modernization, and custom AI implementations. Quantiphi partners with technology giants like AWS, Google Cloud, NVIDIA, and others to drive AI adoption and deliver transformational opportunities for enterprises.

📋 Description

• Design and implement enterprise-grade Generative AI solutions using AWS Bedrock and AgentCore • Define architectures for LLM-based applications, RAG pipelines, and agentic workflows • Develop and orchestrate agentic AI workflows for 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 through APIs and backend services • Design and optimize prompt engineering strategies • Work with structured and unstructured data sources for knowledge-driven AI applications • Evaluate, monitor, and optimize models for latency, cost, and response quality • Collaborate with application, data, and platform teams on end-to-end solution delivery • Define best practices for security, governance, and responsible AI usage • Troubleshoot and resolve production GenAI system issues • Provide technical leadership and mentor team members while remaining hands-on

🎯 Requirements

• 8+ years of relevant hands-on technical experience implementing and developing cloud ML solutions on AWS • Hands-on experience with AWS services, including SageMaker and Bedrock • Experience with SageMaker training jobs and real-time and batch applications • Experience designing and implementing agentic AI architectures using LangChain, Strand Agents, or similar frameworks • Hands-on experience with Amazon AgentCore, including agent memory management, tool registry, and observability • Experience architecting and deploying scalable AI solutions using Lambda, Bedrock, Step Functions, S3, API Gateway, and SageMaker • Proficiency with LLM APIs such as Claude, Nova, and other third-party providers • Experience with API integration and multi-model orchestration strategies • Hands-on experience fine-tuning or optimizing LLMs • Familiarity with LLM tool use, prompt templating, and context management • Strong expertise in vector databases, indexing, embeddings, similarity search, and RAG architectures • Experience evaluating and optimizing LLM zero-shot and few-shot capabilities, hyperparameters, task generalization, and model interpretability • Experience developing and maintaining Model Context Protocol (MCP) implementations • Experience with workflow orchestration tools such as Airflow, Step Functions, SageMaker Pipelines, or Kubeflow • Experience implementing secure, scalable APIs and integrating third-party data sources and tools • Ability to collaborate with developers, QA, project managers, and other stakeholders • Experience with deep learning concepts including Transformers, BERT, attention models, tokenization, and embeddings • Nice to have: software development experience and exposure to frontend/backend frameworks and communication protocols • Nice to have: Infrastructure as Code and CI/CD pipeline experience • Nice to have: NLP concepts including syntactic/semantic analysis and NER

🏖️ Benefits

• Global and diverse culture • Culture built on transparency, diversity, integrity, learning and growth • Remote work (US)

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