Technical Architect – ML, GenAI

Quantiphi

. Design and implement enterprise-grade Generative AI solutions using AWS Bedrock and AgentCore .

Posted 9/15/2026full-timeRemote • United StatesSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing enterprise-grade Generative AI solutions using AWS services, with a strong focus on LLM-based applications, RAG pipelines, and agentic workflows. Proficient in optimizing AI models and integrating LLM capabilities into applications while ensuring security and governance best practices.

Highest-signal resume keywords

AWS BedrockGenerative AI SolutionsLLM-Based ApplicationsRAG PipelinesAgentic Workflows

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Cloud ML SolutionsAWS SageMakerLLM APIsVector DatabasesDeep Learning ConceptsPrompt EngineeringModel OptimizationWorkflow OrchestrationAPI IntegrationAgentCore

Soft Skills

Technical LeadershipCollaborationMentoring

Tools & Technologies

LangChainAirflowStep FunctionsS3API GatewayKubeflow

Industry Keywords

Generative AINLP ConceptsTask AutomationKnowledge-Driven AISecurity Best Practices

Tech Stack

Tools & technologies

AirflowAWSCloud

About the role

Key responsibilities & impact

Design and implement enterprise-grade Generative AI solutions using AWS Bedrock and AgentCore
Define architecture for LLM-based applications, including RAG pipelines and agentic workflows
Develop and orchestrate agentic AI workflows for multi-step reasoning, tool use, and task automation
Build and manage RAG pipelines with 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 security, governance, and responsible AI best practices
Troubleshoot and resolve production GenAI system issues
Provide technical leadership and mentor team members while remaining hands-on

Requirements

What you’ll need

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 AWS 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, including Claude, Nova, and other third-party providers
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 integration
Experience evaluating and optimizing LLM zero-shot and few-shot capabilities, fine-tuning hyperparameters, task generalization, and model interpretability
Experience developing and maintaining Model Context Protocol 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

Comp & perks

Culture built on transparency, diversity, integrity, learning and growth
Environment encouraging innovation and professional and personal growth