Quantiphi

GenAI Architect

Quantiphi

full-time

Posted on:

Location Type: Remote

Location: United States

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Job Level

SeniorLead

Tech Stack

AirflowAWSCloud

About the role

  • 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.

Requirements

  • 8+ years of relevant hands-on technical experience implementing, and developing cloud 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 LangChain, Strand Agents etc., enabling autonomous task planning, decision-making, and multi-step reasoning.
  • Hands-on experience with Amazon AgentCore 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 SageMaker.
  • 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, StepFunctions, SageMaker 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.
Benefits
  • Make an impact at one of the world’s fastest-growing AI-first digital engineering companies.
  • Upskill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues.
  • Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines.
  • Stay ahead of the curve—immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies.
  • Enjoy a fun, diverse and hybrid work culture with ample opportunities to learn and grow.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AWSGenAI solutionsLLM-based applicationsRAG pipelinesagentic workflowsprompt engineeringmodel evaluationfine-tuningDeep Learning ConceptsVector Databases
Soft Skills
technical leadershipmentoringcollaborationproblem-solving