Quantiphi

Senior ML/AI Architect

Quantiphi

full-time

Posted on:

Location Type: Remote

Location: Remote • Massachusetts, New Jersey • 🇺🇸 United States

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Job Level

Senior

Tech Stack

AirflowAzureCloudKubernetesMicroservicesPython

About the role

  • Architect and design enterprise-scale agentic AI platforms, frameworks, and multi-agent workflows
  • Create modular, interoperable, and future-ready AI architectures that integrate seamlessly with existing enterprise systems
  • Lead design of LLM-based applications, RAG systems, multi-agent planning, and autonomous process automation
  • Establish architectural standards, design patterns, and reusable components for AI/ML workloads
  • Oversee end-to-end implementation of AI/ML and agentic systems, including data pipelines, model training, evaluation, and deployment
  • Work closely with engineering teams to ensure delivery of high-performance, scalable, and cost-optimized AI workloads
  • Provide technical leadership for model fine-tuning, orchestration, guardrails, and inference optimization
  • Design secure, compliant, and policy-aligned AI systems with strong guardrails, monitoring, and fallback mechanisms
  • Integrate AI agents and LLM-driven solutions into enterprise applications, APIs, workflow engines, and automation tools
  • Define governance frameworks for model lifecycle management, reliability, safety, and performance tracking
  • Work with business and technology leaders to translate strategic goals into actionable AI roadmaps
  • Advise on platform choices, toolchains, and cloud/edge deployment patterns
  • Prepare technical documents, architectural blueprints, and decision frameworks for leadership
  • Guide data scientists, ML engineers, and developers on solution design, implementation, and best practices
  • Conduct reviews, coach teams, and ensure adherence to ML engineering and MLOps standards

Requirements

  • 10–15+ years of experience in ML/AI engineering, with 4+ years in architect-level roles
  • Strong experience designing LLM-centric systems, including multi-agent architectures, RAG and knowledge-grounded reasoning
  • Workflow orchestration (LangChain, Azure AI Agents, OpenAI Agents, Amazon Bedrock Agents, etc.)
  • Model fine-tuning, prompt engineering, and safety guardrails
  • Expertise across ML infrastructure and MLOps (Kubeflow, Airflow, Vertex AI, Azure ML, Sagemaker, etc.)
  • Strong background in distributed computing, microservices, vector databases, and modern data platforms
  • Hands-on experience with Python, cloud-native architectures, Kubernetes, and API-driven integration
  • Proven ability to build secure, reliable, and scalable AI solutions for large enterprises
  • Deep understanding of compliance, data security, observability, and responsible AI frameworks
  • Ability to create clear architectural documents, diagrams, and technical strategies
Benefits
  • Join a high-growth, AI-first digital engineering and transformation company
  • Work with Fortune 500 clients and cutting-edge market disruptors
  • Collaborate with a talented, dynamic, and driven team
  • Gain exposure to the latest technologies in AI, ML, cloud, and data engineering

Applicant Tracking System Keywords

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

Hard skills
AI architectureLLM-based applicationsmulti-agent workflowsmodel fine-tuningprompt engineeringworkflow orchestrationdistributed computingcloud-native architecturesAPI-driven integrationMLOps
Soft skills
technical leadershipcoachingcommunicationstrategic planningcollaboration