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USA - Remote, United States of America
Remote only
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, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI driving measurable outcomes at the very core of their operations.
Since our founding in 2013, Quantiphi has tackled some of the world’s most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value, not just technology for technology’s sake.
Headquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc. As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact.
We’ve been recognized with:
21x 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.
Job Opening:
Role: AI Platform/AIOps Architect
Experience Level: 10+ Years
Work location: Chicago, IL or from Surrounding States
Key Skills:
10+ years working in ML/AI platform engineering or AI/MLOps roles with strong architecture exposure.
Strong expertise in the Google Cloud (GCP) native AI/ML stack, including: Vertex AI (primary), Google Kubernetes Engine (GKE), Cloud Functions, AutoML, Vertex AI Pipelines, BigQuery ML, API Gateway, and CI/CD (Cloud Build/Cloud Deploy or equivalent).
Hands-on experience with MLOps toolset and awareness of: MLflow, Kubeflow, Vertex AI Pipelines, Airflow, BentoML, KServe, Seldon.
Deep understanding of model lifecycle management (feature engineering -> training -> registry -> deployment -> monitoring).
Experience implementing or supporting LLMOps pipelines, including prompt versioning, evaluation metrics, and automation frameworks.
Deep understanding of the ML lifecycle: data ingestion, feature engineering, training, evaluation, model packaging, CI/CD, drift detection, monitoring, and governance.
Strong experience with Google Cloud's Vertex AI platform, including Pipelines, Feature Store, Model Registry, and Model Monitoring.
Experience implementing ML CI/CD pipelines including automated training, testing, validation, model promotion, and endpoint deployment.
Strong SQL and data transformation experience using Snowflake, Databricks, Spark.
Experience with feature engineering pipelines and Feature Store management.
Understanding of lineage tracking: training data snapshot, feature versions, code versioning, metadata tracking, and reproducibility.
Hands-on experience with Vertex AI Foundation Models, OpenAI, Anthropic, or Llama models.
Experience with Cloud Monitoring, Vertex AI Model Monitoring, Prometheus/Grafana.
Strong foundation in Python and cloud-native development patterns.
Solid understanding of security best practices, Cloud IAM, secrets management, and artifact governance.
Responsibilities:
Architect and implement the MLOps strategy for the program, ensuring alignment with the project proposal and delivery roadmap.
Design and own enterprise-grade ML/LLM pipelines covering model training, validation, deployment, versioning, monitoring, and CI/CD automation using GCP-native services.
Build container-oriented ML platforms (GKE-first) while evaluating alternative orchestration tools with similar capabilities (Kubeflow, Vertex AI, MLflow, Airflow, etc.).
Implement hybrid MLOps + LLMOps workflows, including prompt/version governance, evaluation frameworks, and monitoring for LLM-based systems within the GCP environment.
Serve as a technical authority across multiple internal and customer projects, contributing architectural patterns, best practices, and reusable frameworks for GCP.
Enable observability, monitoring, drift detection, lineage tracking, and auditability across ML/LLM systems using tools like Cloud Monitoring and Vertex AI Model Monitoring.
Collaborate with cross-functional teams — data engineering, platform, DevOps, and client stakeholders — to deliver production-ready ML solutions on Google Cloud.
Ensure all solutions adhere to security, governance, and compliance expectations, particularly around handling GCP services, Google Kubernetes Engine workloads, and MLOps tools.
Conduct architecture reviews, troubleshoot complex ML system issues, and guide teams through implementation across cloud-native ML platforms on GCP.
Mentor engineers and provide guidance on modern MLOps tools, Vertex AI platform capabilities, and best practices.
Travel Required - upto 30%
What is in it for you:
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
