Jobs at Quantiphi

Lead cloud migration and platform engineering efforts, designing AWS architectures and migration plans from on-prem VMware to AWS. Perform migration assessments, tooling selection, wave planning, dependency analysis, security/compliance alignment, OS and database troubleshooting, and optimize post-migration performance while collaborating with stakeholders and platform teams.

Designs and builds Azure-based data pipelines, streams, hybrid data solutions, and terabyte-scale ingestion systems. Develops production-quality code for distributed ML workflows, troubleshoots complex systems, optimizes SQL, and supports data solution modernization. Responsibilities include technical documentation, deployment, post-production support, testing, migration coordination, and collaboration with architects, analysts, engineers, vendors, and business teams.

Leads enterprise CCaaS and customer experience transformation sales, from opportunity qualification through solutioning and deal closure. Develops CX strategies, architectures, roadmaps, and AI-driven use cases involving conversational AI, agent assist, analytics, and omnichannel engagement. Builds executive customer relationships, delivers technical and business presentations, manages complex stakeholders and partner ecosystems, and collaborates with architecture, data science, and engineering teams. The role requires 50% travel to customer sites and industry events.

Leads software product development projects and advanced analytics, machine learning, and technology solution delivery. Responsibilities include gathering requirements, defining problems, creating user stories, managing project teams and client expectations, preparing technical documentation, applying Agile and Scrum methodologies, identifying risks, consulting clients, and developing creative solutions and presentations.

Administer and optimize Workday HCM, including business processes, workflows, calculated fields, security, reports, dashboards, tenant configuration, and release management. Partner with stakeholders to implement enhancements, troubleshoot issues, perform testing, maintain system integrity, and support end users. The role also requires ticketing and case management experience, strong analytical and communication skills, and familiarity with multiple Workday modules.

Leads data preparation, profiling, and exploratory analysis for large-scale datasets; builds, evaluates, tunes, and deploys time-series forecasting models for demand planning. The role requires Python, SQL, AWS, SageMaker, ML frameworks, and MLOps tools. It involves independent end-to-end ownership, customer presentations, stakeholder collaboration, and translating technical work into business outcomes. Retail or e-commerce forecasting and computer vision experience are preferred. Travel to the Bengaluru client office twice weekly is required.

Develop and fine-tune traditional machine learning and predictive models for regression, classification, sales forecasting, and growth prediction. Prepare and unify data from multiple sources, perform exploratory data analysis and feature engineering, evaluate model performance, and use Python, Jupyter, and AWS services including S3 and Redshift. Present model outputs and insights to business stakeholders while working independently with client teams.

Designs and scales distributed platform services, APIs, microservices, and React applications for healthcare technology platforms. Owns architecture, reliability, performance, testing, CI/CD, observability, infrastructure, and production support. Partners with product and clinical teams, mentors engineers, leads technical decisions, and uses AI-augmented development tools. Requires extensive software engineering experience with cloud-native systems, databases, REST APIs, frontend frameworks, and scalable SaaS platforms.

Architects and develops scalable Java and Spring Boot web applications, RESTful APIs, and database-backed systems. Leads software delivery, testing, code reviews, automation, troubleshooting, security remediation, telemetry, production incident response, and root-cause resolution. Collaborates with stakeholders and cross-functional teams while modernizing application stacks. The role also supports cloud-native architecture, CI/CD, container orchestration, and AI-augmented development.

Architects, develops, tests, and optimizes scalable Java-based web applications using Spring Boot microservices and modern frontend frameworks. Leads software delivery across the full lifecycle, including API design, technical specification refinement, automation, performance optimization, test-driven development, code reviews, and troubleshooting. Collaborates with internal teams and external partners to deliver maintainable solutions, improve engineering workflows, and uphold modern architecture and development standards. The role is remote in Canada and requires working Eastern Time hours.

Architect, develop, deploy, and monitor scalable machine learning and LLM-powered conversational AI systems on AWS. Lead agent framework, tool-calling, multi-agent, RAG, MLOps, analytics, and observability development while collaborating with technical and business stakeholders.

Build and maintain large-scale Snowflake data platforms and pipelines, including AWS and legacy-platform migrations. Develop SQL, Spark, PySpark, and Python transformations; implement batch and streaming workflows; optimize Snowflake performance; and apply security, governance, and data-sharing capabilities. Support migration validation, troubleshooting, monitoring, production operations, SDLC, CI/CD, and stakeholder collaboration while using Snowflake AI and migration tools.

Design and deliver enterprise-grade generative AI solutions on AWS using Bedrock, AgentCore, SageMaker, LLMs, RAG pipelines, vector databases, and agentic workflows. Build scalable APIs and integrations, optimize prompts and models, evaluate performance, and implement security and governance. Collaborate with application, data, and platform teams, troubleshoot production systems, define best practices, and mentor engineers while remaining hands-on.

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.

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.

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.