Quantiphi
Associate Tech Architect - ML
USA - Remote
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About the role
- Quantiphi is seeking an experienced Associate Architect - Machine Learning Engineering (MLE) to design and deliver scalable AI/ML platforms, developer frameworks, and Agentic AI solutions for enterprise applications.
- In this role, you will provide technical leadership in building production-grade machine learning systems, evolving Python SDK frameworks, and enabling intelligent autonomous workflows.
- You will work closely with product, platform, and engineering teams to define architecture, establish best practices, and build highly scalable AI solutions leveraging modern agentic frameworks.
Responsibilities
- Design scalable Agentic AI architectures and multi-agent systems capable of orchestrating complex business workflows with minimal human intervention.
- Lead the design and implementation of reusable AI platform components, ensuring high performance, reliability, and security.
- Build and optimize high-performance RESTful APIs using FastAPI to support AI services, inference pipelines, and autonomous agents.
- Design and implement CI/CD pipelines using Jenkins and GitLab Runners to automate testing, deployment, and release management.
- Partner with Data Science, Product, Platform Engineering, and Cloud teams to translate business requirements into scalable technical solutions.
- Drive architectural decisions around scalability, resiliency, performance optimization, and software lifecycle management.
- Support production environments by troubleshooting complex distributed systems and ensuring high platform availability.
- 21x Google Cloud Partner of the Year awards in the last 8 years.
- 3x NVIDIA Partner of the Year titles.
- 2x Snowflake Partner of the Year awards.
Requirements
- Hands-on experience designing and implementing Agentic AI workflows and multi-agent systems.
- Strong understanding of LLM orchestration, autonomous agents, and AI workflow automation.
- Experience creating reusable frameworks, libraries, and tooling used across engineering organizations.
- Experience with release automation, artifact management, and deployment strategies.
- Experience using Galileo for AI evaluation, observability, and production monitoring.
- Knowledge of monitoring AI systems, debugging model behavior, and improving production performance.
- Strong understanding of microservices architecture, system scalability, security, and performance optimization.
- Experience with LLM-based applications and Agentic AI platforms.
- Experience with Docker and Kubernetes.
- Knowledge of cloud platforms such as AWS, Google Cloud Platform (GCP), or Azure.
- Experience with MLOps tools and production ML deployment.
- Experience with distributed systems and event-driven architectures.
- Contributions to open-source AI, Python SDK, or Agentic AI projects.
- Experience with infrastructure-as-code (Terraform or similar).
- 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.
Benefits
- We offer first-in-class industry solutions across Healthcare, Financial Services, Consumer Goods, Manufacturing, and more, powered by cutting-edge Generative AI and Agentic AI accelerators.
- Mentor Machine Learning Engineers through technical guidance, design reviews, and best practices.
Company info
- Be part of a trailblazing team that's shaping the future of AI, ML, and cloud innovation.
This listing is sourced directly from Quantiphi's careers page and normalized into a canonical job model.