Company Profile

Quantiphi is an award-winning Data Science and Machine Learning Software and Services Company focused on helping organizations translate the big promise of Machine Learning technologies into quantifiable business impact. We were founded on the belief that machine learning and artificial intelligence are transformative technologies that will create the next quantum gain in customer experience and unit economics of businesses. We are one of the five global launch partners for Google in Machine Learning and one of the three global launch partners for the Google Cloud Contact Center AI solution.

Our signature approach combines ground-breaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.

We believe in “Solving What Matters”

Company Highlights

- Quantiphi has seen 2.5x growth YoY since its inception in 2013
- Winner of the “Machine Learning Partner of the Year” award from Google for two consecutive years - 2017 & 2018
- Winner of the “Social Impact Partner of the Year” award from Google in 2019 Winner of the “Data & Analytics - Specialisation Partner of the Year” and “US Education - Public Sector Partner of the Year” award for 2020

Role - Associate Architect - Machine Learning Engineer

Experience level - 6 to 10 years

Location - Mumbai & Bangalore (Hybrid)

Job Summary

As an Associate Technical 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 explicit 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

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

📌 Associate Technical Architect ML (Bengaluru)
🏢 Quantiphi
📍 Bengaluru