[Remote] Associate Tech Architect - ML
Note: The job is a remote job and is open to candidates in USA. Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. The Associate Architect – Machine Learning Engineering (MLE) will design and deliver scalable AI/ML platforms and provide technical leadership in building production-grade machine learning systems.
Responsibilities
- Architect and evolve enterprise-grade Python SDK frameworks that improve developer productivity, extensibility, and maintainability across AI platforms
- 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
- Define architectural standards, coding guidelines, and engineering best practices for ML platforms and SDK development
- 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
- Establish observability, monitoring, and evaluation strategies using Galileo to improve model quality, agent performance, and production reliability
- Drive architectural decisions around scalability, resiliency, performance optimization, and software lifecycle management
- Mentor Machine Learning Engineers through technical guidance, design reviews, and best practices
- Evaluate emerging AI technologies and recommend architectural improvements to enhance enterprise AI capabilities
- Support production environments by troubleshooting complex distributed systems and ensuring high platform availability
Skills
- Expert-level proficiency in Python with extensive experience building enterprise-grade machine learning applications
- Strong experience designing scalable APIs using FastAPI
- Deep understanding of software engineering principles, object-oriented programming, and API design
- Hands-on experience designing and implementing Agentic AI workflows and multi-agent systems
- Experience building production-ready AI applications using modern Agentic Frameworks
- Strong understanding of LLM orchestration, autonomous agents, and AI workflow automation
- Extensive experience developing and maintaining Python SDKs or internal developer platforms
- Experience creating reusable frameworks, libraries, and tooling used across engineering organizations
- Strong experience implementing automated CI/CD pipelines using Jenkins and GitLab Runners
- 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
- Proven experience designing scalable, cloud-native AI platforms and distributed machine learning systems
- Strong understanding of microservices architecture, system scalability, security, and performance optimization
- Strong architectural thinking with excellent problem-solving abilities
- Ability to lead technical discussions and influence architectural decisions across teams
- Excellent communication and stakeholder management skills
- Proven ability to mentor engineers and foster technical excellence
- Ability to independently drive large-scale engineering initiatives from design through production
- 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)
Company Overview
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