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!
About Quantiphi:
Quantiphi is an award-winning Applied AI and Big Data software and services company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.
Quantiphi has seen 2.5x growth YoY since its inception in 2013, we don’t just innovate - we lead.
Headquartered in Boston, with 4,000+ professionals across the globe. Quantiphi leverages Applied AI technologies across multiple a. Industry Verticals (Telco, BFSI, HCLS etc.) and is an established Elite/Premier Partner of NVIDIA, Google Cloud, AWS, Snowflake, and others.
We’ve been recognized with:
17x Google Cloud Partner of the Year awards in the last 8 years.
3x AWS AI/ML award wins.
3x NVIDIA Partner of the Year titles.
2x Snowflake Partner of the Year awards.
We have also garnered top analyst recognitions from Gartner, ISG, and Everest Group.
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.
We have been certified as a Great Place to Work for the third year in a row- 2021, 2022, 2023.
Be part of a trailblazing team that’s shaping the future of AI, ML, and cloud innovation.
Your next big opportunity starts here!
For more details, visit: Website or LinkedIn Page.
Role: Architect Data Engineer - AI Platforms
Experience Level: 10+ yrs
Work Location: US East/Canada (Remote)
Role Overview:
Lead the architectural vision for a next-generation data layer designed specifically for Agentic AI. You will define high-performance schemas, orchestrate complex hybrid-database environments (Snowflake/Kinetica/NoSQL), and serve as the primary technical liaison for our customers. This is a high-visibility role blending deep technical governance with strategic relationship development.
Key Responsibilities:
System Architecture: Design the end-to-end blueprint for a modern data layer that seamlessly integrates structured, unstructured, and relational (Graph) data for AI agents.
Schema & Ontology Design: Define multi-tenant schemas and Knowledge Graph ontologies that allow LLM agents to perform complex reasoning and cross-domain data retrieval.
Database Administration & Governance: Oversee the health, security, and performance optimization of our data clusters (Snowflake/Kinetica), ensuring 99.9% availability for mission-critical AI workflows.
Strategic Client Fronting: Act as the "Face of Engineering" for the customer. Lead discovery workshops, manage technical expectations, and align the architectural roadmap with their business objectives.
Performance Engineering: Define performance and observability standards to ensure low-latency, accurate, reliable data retrieval for real-time agentic AI workloads.
Basic Qualifications:
System Architecture: Design the end-to-end blueprint for a modern data layer that seamlessly integrates structured, unstructured, and relational (Graph) data for AI agents.
Schema & Ontology Design: Define multi-tenant schemas and Knowledge Graph ontologies that allow LLM agents to perform complex reasoning and cross-domain data retrieval.
Database Administration & Governance: Oversee the health, security, and performance optimization of our data clusters (Snowflake/Kinetica), ensuring 99.9% availability for mission-critical AI workflows.
Strategic Client Fronting: Act as the "Face of Engineering" for the customer. Lead discovery workshops, manage technical expectations, and align the architectural roadmap with their business objectives.
Performance Engineering: Establish benchmarks for data latency and retrieval accuracy, ensuring the data layer can keep pace with the real-time demands of agentic execution.
The Hybrid Stack: Proven expertise in architecting for Snowflake (Data Cloud) and Kinetica (Real-time/Vector/OLAP).
Knowledge Graph Mastery: Ability to design Property Graphs or RDF schemas that map enterprise entities into a machine-readable "World Model."
Advanced ETL/ELT Strategy: Deep knowledge of data orchestration patterns (Change Data Capture, Streaming, and Batch) to ensure data freshness.
Database Internals: Strong DBA skills—partitioning strategies, indexing, vacuuming, and resource scaling in cloud-native environments.
Good to Have (The “Agentic” Edge):
Semantic Layer Design: Experience with tools like Cube or dbt Semantic Layer to provide a consistent "Language" for AI agents to query.
Security & Privacy: Knowledge of RBAC and Row-Level Security (RLS) within an AI context—ensuring agents only "see" what they are authorized to access.
Tooling for Agents: Experience designing API-first data layers that agents can use as "Tools" (e.g., function calling).
What’s in it for YOU at Quantiphi:
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.
Stay ahead of the curve—immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Skills Required
- 10+ years experience in data engineering or architecture
- Design end-to-end modern data layer integrating structured, unstructured, and graph data
- Define multi-tenant schemas and Knowledge Graph ontologies for LLM agents
- Experience administering and governing Snowflake and Kinetica clusters ensuring high availability
- Client-facing technical leadership: run discovery workshops and align architecture with business goals
- Performance engineering for low-latency, reliable data retrieval for real-time AI workloads
- Proven expertise architecting for Snowflake (Data Cloud) and Kinetica (real-time/vector/OLAP)
- Knowledge Graph mastery: design Property Graphs or RDF schemas mapping enterprise entities
- Advanced ETL/ELT strategy experience including Change Data Capture, streaming, and batch patterns
- Strong DBA skills: partitioning, indexing, vacuuming, and resource scaling in cloud-native environments
- Establish benchmarks and observability standards for data latency and retrieval accuracy
Quantiphi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Quantiphi and has not been reviewed or approved by Quantiphi.
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Wellbeing & Lifestyle Benefits — Wellbeing initiatives such as monthly meeting-free AMA-Zen Days, health check-ups, and wellness counseling are designed to reduce burnout and support day-to-day balance. Broader wellness programs reinforce both physical and mental health.
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Flexible Benefits — Remote/hybrid options with flexible working hours provide meaningful autonomy over where and when work gets done. Flexible leave constructs, including sabbaticals and special day leaves, add practical adaptability to the package.
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Parental & Family Support — Paid parental leave in the U.S., alongside maternity and childcare support, signals solid backing for families. These family-oriented policies integrate with a wider health and wellness focus.
Quantiphi Insights
What We Do
Quantiphi is an award-winning AI-first digital engineering company driven by the desire to solve transformational problems at the heart of business. Quantiphi solves the toughest and complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve quantifiable business impact at unprecedented speed.
