Jobs at Quantiphi

Design and lead large-scale AWS migrations (rehost/replatform), architect cloud infrastructure and platforms, automate migrations with IaC and scripting, troubleshoot OS/database issues, and implement hybrid networking and security best practices.

Architect and implement enterprise-grade MLOps/LLMOps platforms on AWS and Kubernetes. Design ML/LLM pipelines for training, validation, deployment, monitoring, governance, CI/CD, and observability. Serve as technical authority, conduct architecture reviews, ensure security and compliance, and mentor engineering teams across projects.

Design, develop, and maintain secure, scalable web applications and backend APIs. Analyze applications hosted on GKE, data sources, REST integrations, and Argo CD deployment strategies. Define AWS architecture and migration roadmaps for moving Kubernetes workloads and PostgreSQL databases from GKE to EKS. Lead technical solution development, troubleshoot issues, communicate with clients, and guide developers through implementation.

Design and build large-scale data pipelines, cloud migration strategies, and storage and processing solutions using Azure Synapse Analytics. Develop ETL/ELT pipelines, ingest terabytes or petabytes of data, optimize distributed systems, and create automation, monitoring, and administration tooling. Collaborate with cloud, infrastructure, engineering, DevOps, and customer teams to deliver production-grade healthcare data platforms.

Design, develop, maintain, and troubleshoot secure, scalable web applications. Analyze backend REST APIs, data sources, deployments, and Kubernetes-hosted applications. Design AWS architectures and migration strategies from Google Kubernetes Engine to Amazon EKS, including PostgreSQL databases. Lead technical solution development, communicate with clients, and guide developer teams through implementation.

Maintain platform stability through Tier-1 incident resolution, system monitoring, alerting, runbook execution, SLA adherence, reporting, and escalation. Build and maintain scalable Kubernetes and container infrastructure, CI/CD pipelines, deployment strategies, health checks, and observability. Develop production-grade Python services using Flask and Gunicorn, integrating databases and streaming systems such as Redis and Kafka. Support Linux environments, video-processing workloads, scheduled maintenance, and rotational operations shifts.

Build, deploy, and maintain production-grade machine learning systems on Google Cloud Platform. Develop generative AI applications, RAG systems, agentic and multi-agent workflows, traditional ML, and computer vision solutions. Own MLOps practices including CI/CD, testing, model versioning, deployment, monitoring, and drift detection. Build APIs, microservices, knowledge graphs, and semantic search systems while collaborating with architects, data engineers, analysts, and enterprise clients.

Leads platform engineering architecture for scalable, secure, highly available AWS solutions. Designs pipeline infrastructure and integrations across RPA processes, ERP and third-party applications, internal services, and downstream systems. Defines API, IAM governance, networking, infrastructure-as-code, CI/CD, DevSecOps, monitoring, observability, disaster recovery, and integration architectures. Provides technical leadership, stakeholder management, documentation, architecture reviews, mentoring, and engineering best practices in a remote Canadian environment.

Design and develop enterprise Master Data Management solutions using Profisee, Informatica MDM, or Reltio. Build scalable ingestion, integration, transformation, ETL/ELT, and publishing pipelines; implement cleansing, matching, deduplication, survivorship, hierarchy, and data quality rules. Integrate MDM platforms with databases, APIs, data lakes, warehouses, and applications. Troubleshoot production issues, maintain mappings and documentation, collaborate with stakeholders, support delivery activities, and mentor junior data engineers.

Develop machine learning architectures, models, data pipelines, and production systems using Python, PySpark, SQL, AWS, NLP, LLMs, and Generative AI. Collaborate with engineers, analysts, delivery managers, and clients to deliver measurable business outcomes. Communicate insights, identify sales opportunities, mentor junior engineers, manage client relationships, and support project delivery.

Develop high-level machine learning architectures, build and productionize models and end-to-end ML systems, and deliver data-driven insights for clients. The role involves Python, PySpark, SQL, NLP, LLM, GenAI, statistical modeling, cloud services, and data pipeline development. Responsibilities also include client relationship management, mentoring junior engineers, coordinating delivery teams, identifying sales opportunities, and communicating business impact.

Owns growth and P&L responsibility for strategic UK insurance accounts. Develops account plans, identifies new business and cross-sell opportunities, manages executive relationships, sells AI, data, cloud, and digital transformation solutions, and oversees the full sales cycle through contract negotiation and delivery coordination. The role manages revenue portfolios exceeding £5 million and travels 30–50% to client sites, conferences, and related events.

Senior technical sales and solutions leader responsible for architecting end-to-end AI solutions, advising strategic clients, shaping AI roadmaps, and leading technical sales cycles from discovery through production. The role requires expertise in generative and agentic AI, cloud architecture across GCP, AWS, and Azure, value-based commercial models, executive presentations, business analysis, and reusable AI asset development. The partner also mentors AI talent and contributes to go-to-market and company strategy.

Designs and leads large-scale on-premises-to-AWS migrations, including rehost and replatform initiatives. Responsibilities include architecting multi-account AWS infrastructure, assessing migration portfolios, troubleshooting Windows/Linux and database systems, configuring hybrid networks, automating migration and deployment processes with Python, Bash, Terraform, and CloudFormation, and implementing security, monitoring, container platforms, and CI/CD pipelines.

Design and optimize enterprise data architectures and pipelines using SQL, Spark/PySpark, Python, Apache Iceberg, AWS, ClickHouse, and PostgreSQL. Build greenfield application and data solutions, optimize databases and Spark jobs, integrate data virtualization and governance tools, and support CI/CD and infrastructure-as-code practices. Experience with financial services workloads is valued, while telecommunications knowledge is preferred but not required.

Lead AWS workload migrations from on-premises and VMware environments, including rehosting virtual machines to EC2. Design hybrid cloud networks, landing zones, and secure AWS architectures; automate migration and deployment processes with Python, Bash, Terraform, CloudFormation, and CI/CD tools. Troubleshoot Windows and Linux systems, configure load balancing, support database and container migrations, monitor performance, and apply security, compliance, configuration management, and Agile DevOps practices.

Designs and maintains high-volume HL7 and FHIR ingestion pipelines, secure Epic and hospital integrations, data validation systems, and compliant healthcare data exchanges. Builds enterprise SaaS microservices using ReactJS, Python, and AWS services; optimizes distributed and hybrid-cloud environments; leads testing, code reviews, production troubleshooting, architecture documentation, and customer communications. Preferred experience includes Epic App Orchard, healthcare integration engines, clinical workflows, GenAI/ML, DevOps, data pipelines, and NoSQL.

Design and optimize enterprise data architectures, pipelines, and application workloads using SQL, Spark/PySpark, Python, Apache Iceberg, AWS, ClickHouse, and Aurora PostgreSQL. Build integrations with data virtualization and governance tools, support greenfield projects, optimize databases and Spark jobs, and collaborate on cloud, infrastructure-as-code, and CI/CD initiatives. Experience serving financial services and insurance customers is valuable, while telecommunications knowledge is preferred.

Architect and implement scalable AWS data warehouses, data lakes, lakehouses, and resilient data pipelines. Lead solutions using AWS analytics, storage, processing, integration, governance, orchestration, and database services. Develop with Python, PySpark, and SQL; optimize schemas, queries, partitioning, indexing, and performance. Support legacy and on-premises migrations to AWS, collaborate with globally distributed teams, and contribute to enterprise application workloads and financial-services use cases.

Design and develop advanced machine learning and generative AI solutions, including LLM fine-tuning, RAG architectures, prompt engineering, model evaluation, and MLOps. Architect scalable training, deployment, and retraining workflows on AWS using SageMaker and related services. Collaborate with engineering, QA, project management, and other stakeholders to deliver reliable AI applications and solve complex business problems.