Architect Machine Learning

Designation: Architect - Machine Learning

Experience Level: 9-17 years

Job Location: Bangalore/ Mumbai/ Trivandrum (Hybrid)

Job Summary:

As a Technical Architect at Quantiphi, you are a senior technical leader who governs the quality

and strategic direction of our most critical AI initiatives on Google Cloud Platform. You'll design

complex, enterprise-grade AI platforms spanning generative AI, agentic systems, traditional ML,

and computer vision while influencing how we architect solutions across the entire practice. This

role is for seasoned architects who establish standards, serve as trusted advisors to C-level

executives, and drive technical excellence at scale.

Responsibilities:

Enterprise Architecture & Leadership:

• Design and govern large-scale, mission-critical AI platforms meeting 99.99%+ availability, security, scalability, and compliance requirements
• Define integration patterns for embedding AI across complex enterprise ecosystems including legacy systems and cloud applications
• Establish architectural standards, conduct architecture reviews, and manage technical debt across engagements
• Act as lead technical advisor for strategic client accounts, building relationships with CTOs, VPs, and Chief AI Officers

Generative AI & Agentic Platform Architecture:

• Define enterprise architectures for agentic systems, multi-agent platforms, and autonomous workflow orchestration at scale
• Architect knowledge management and semantic search as integrated enterprise capabilities
• Design model governance with formal approval workflows, compliance controls, and audit logging

Traditional ML & Computer Vision Architecture:

• Establish reference architectures for forecasting, recommendations, and statistical modeling at enterprise scale
• Design feature platforms and serving infrastructure for diverse ML use cases
• Architect scalable computer vision platforms for document processing and visual analytics

Standards & Governance:

• Establish comprehensive LLMOps and MLOps standards for prompt engineering, model versioning, CI/CD, evaluation, and production monitoring
• Design AI security architectures for regulated industries implementing OWASP LLM Top 10 and data protection requirements
• Create reusable frameworks and reference architectures that accelerate project delivery

Client & Practice Leadership

• Lead pre-sales for strategic deals including solution design and effort estimation
• Mentor Associate Technical Architects and senior engineers; guide strategic technology decisions
• Contribute to thought leadership through whitepapers, case studies, and best practice documentation

Required Qualifications:

• Master's degree in Computer Science, Engineering, or related field (or equivalent extensive demonstrated expertise)
• 10-15 years of progressive AI/ML experience with 5+ years in senior architecture and technical leadership roles
• Track record architecting and delivering large-scale AI platforms for Fortune 500 enterprises
• Proven experience as trusted technical advisor to C-level stakeholders (CTOs, VPs,Chief AI Officers) on technology strategy
• Deep expertise in enterprise architecture: system integration, legacy modernization, cloud-native design, and compliance
• Comprehensive knowledge of cloud ML platforms with strong GCP expertise
• Strong command of enterprise AI architectures spanning agentic systems, RAG, multi-agent platforms, knowledge management, traditional ML, and computer vision
• Expertise in AI security, compliance architectures, and regulatory requirements (HIPAA, GDPR, SOC 2, PCI-DSS)

Preferred Qualifications:

• Google Cloud Professional Cloud Architect and Machine Learning Engineer certifications
• Published thought leadership including whitepapers, technical blogs, or conference presentations
• Deep industry expertise in Financial Services, Healthcare, or highly regulated industries
• Experience translating AI research into production systems

What Sets This Role Apart:

• Shape AI strategy for Fortune 500 enterprises across multiple domains through your
• architectural decisions.
• Build trusted advisor relationships with C-level executives guiding critical technology transformations.
• Establish technical standards and patterns that guide dozens of projects and hundreds of engineers.
• Tackle complex challenges designing novel solutions that push enterprise AI boundaries while navigating real-world constraints.