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Associate Architect - Machine Learning
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While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
As an Associate Architect at Quantiphi, you will design comprehensive technical solutions for enterprise AI initiatives, partnering with Fortune 500 clients on Google Cloud Platform. You'll translate complex business requirements into scalable architectures spanning generative AI, traditional ML, and computer vision. This role is for systems thinkers who architect multi-component AI platforms, mentor engineering teams, and build trusted advisor relationships with stakeholders.
Responsibilities:
Solution Architecture & Design
- Lead technical architecture for enterprise AI solutions, creating design documents, architecture diagrams, data flows, and integration blueprints.
- Define integration strategies between AI systems and enterprise infrastructure (data warehouses, business applications, legacy systems).
- Conduct feasibility assessments, proof-of-concept evaluations, and build-versus-buy analyses.
- Design multi-workstream AI platforms with clear separation of concerns and enterprise-grade reliability Generative AI & Agentic Architecture.
- Architect RAG systems defining chunking strategies, embedding selection, retrieval patterns, and vector database choices.
- Design multi-agent systems with clear orchestration patterns, agent communication protocols, and reliable coordination.
- Architect knowledge graph solutions integrated with RAG for enterprise knowledge management and semantic discovery.
Traditional ML & Computer Vision Architecture
- Architect production ML pipelines for forecasting, recommendations, and statistical modeling; design feature engineering and model selection strategies.
- Architect scalable computer vision systems for document processing, image understanding, and visual analytics.
- Establish model evaluation frameworks, validation strategies, and monitoring approaches for diverse ML applications.
MLOps & Governance
- Design ML governance frameworks with model versioning, approval workflows, compliance logging, and audit trails.
- Define CI/CD pipelines for ML development using cloud-native tools with automated testing and validation gates.
- Create LLMOps standards for prompt versioning, evaluation, and cost optimization.
- Establish AI safety practices including guardrails, output filtering, and bias detection.
Client Engagement & Leadership
- Present architecture solutions to client stakeholders, articulating design trade-offs and technical challenges.
- Partner on RFPs and pre-sales solution design; mentor senior ML engineers on architecture principles.
- Define architectural standards and best practices for project teams.
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or related field (or equivalent demonstrated expertise).
- 6-10 years of progressive ML/AI experience with 2+ years in architecture and technical leadership roles.
- Portfolio of successfully architected and delivered production AI/ML solutions in client-facing environments.
- Proven client-facing experience including architecture presentations and technical advisory roles.
- Deep expertise architecting across multiple domains: generative AI, RAG, multi-agent systems, traditional ML, and computer vision.
- Strong understanding of enterprise architecture principles, cloud-native design, and distributed systems.
- Experience designing production ML systems including model monitoring, serving infrastructure, and governance.
- Hands-on experience with ML security, compliance, and data privacy in regulated environments.
Preferred Qualifications:
- Google Cloud Professional Cloud Architect or Machine Learning Engineer certification.
- Successful pre-sales or architecture leadership track record.
- Domain expertise in Financial Services, Healthcare, Retail, or Manufacturing.
- Experience with knowledge graphs and semantic search implementations
What Sets This Role Apart:
- Shape AI strategy for Fortune 500 enterprises across multiple AI/ML domains through your architectural decisions.
- Build trusted relationships with client technical leaders while serving as a subject matter expert.
- Bridge technical excellence with business impact - translating cutting-edge AI capabilities and proven ML approaches into pragmatic solutions that deliver measurable value.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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