Jobs at Quantiphi

Serve as a technical advisor for strategic clients, architecting AI solutions and technology roadmaps. Lead customer presentations, demonstrations, proofs of concept, and technical sales cycles, particularly on Google Cloud. Translate complex AI concepts into business value, overcome technical objections, influence product and company strategy, develop new opportunities, and mentor AI talent. Requires strong expertise in generative AI, computer vision, cloud architecture, executive communication, quantitative analysis, and consultative selling.

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.

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.

Develop, modernize, and support enterprise Java applications using Spring Boot, AWS, microservices, REST and SOAP APIs. Design cloud-native solutions, integrate APIs, deploy and debug applications, perform testing, troubleshoot production issues, and apply application security practices. Collaborate with clients and distributed teams, document technical requirements, prioritize project targets, mentor team members, and contribute to architecture, customer delivery, and continuous improvement.

Lead enterprise SEO and GEO/AEO initiatives to increase organic traffic, search visibility, conversions, and AI search presence. Responsibilities include SEO strategy, keyword and content analysis, technical audits, content optimization, website migration support, analytics reporting, dashboard creation, and cross-functional collaboration with content, engineering, design, product marketing, and analytics teams.

Design and evaluate quantum, quantum-inspired, and hybrid quantum-classical engineering solutions for business problems. Build proofs of concept, reusable code, benchmarks, and scalable machine learning workflows. Translate business needs into quantum-relevant formulations, collaborate across research and client teams, contribute to technical publications and patents, mentor junior staff, and support architecture, code reviews, technical discussions, and innovation initiatives.

Supports offshore professional services delivery operations by tracking resource demand, preparing profiles, coordinating interviews, onboarding resources, maintaining Workday project and timesheet data, validating billing, updating dashboards, and producing delivery reports. The role requires accurate tracker management, stakeholder follow-up, data collection, compliance monitoring, and ad hoc reporting while coordinating across US, European, and offshore teams.

Design, develop, and maintain UI and API automation for AI/ML and generative AI applications. Own end-to-end testing (functional, integration, regression), validate model outputs (accuracy, relevance, safety, hallucinations), build reusable frameworks, integrate tests into CI/CD, collaborate with engineering and product teams, and mentor junior engineers to promote automation-first AI quality practices.

Design and deliver large-scale data pipelines and storage/compute solutions on Google Cloud. Build ingestion and processing jobs for terabyte/petabyte workloads, create cloud migration strategies, troubleshoot distributed systems, and develop automation, testing, and monitoring tooling. Collaborate with cloud, software, ML, and operations teams and contribute to proposals and solution designs while ensuring data modeling and governance.

Design and implement scalable enterprise data platforms, ETL/ELT pipelines, data warehouses and lakes. Define data models, governance, security, and architecture standards. Collaborate with product, BI, and data science teams, provide production support, mentor engineers, and evaluate emerging technologies and POCs.

Leads requirements gathering, process mapping, data analysis, solution design, stakeholder communication, and testing support for healthcare provider technology projects. Focus areas include EHR integration, revenue cycle management, patient engagement, clinical workflows, compliance, interoperability, and value-based care. Creates project documentation, supports UAT, manages business and technical alignment, and mentors junior analysts.

Lead Oracle database migrations to AWS, ensuring minimal downtime and optimized performance. Responsibilities include database tuning, pipeline building, and managing S3 data lakes.

Lead platform architecture for cloud-based solutions, design scalable secure AWS platforms and integrations, define IaC and CI/CD pipelines, implement IAM governance, observability, and automation, and provide technical leadership and stakeholder management.

The role involves leading automation strategy and framework development, executing automation projects, mentoring engineers, and ensuring integration with CI/CD pipelines while driving innovation in testing practices.

The Associate Lead will oversee QA and MLOps for AI systems, defining testing strategies, validating ML lifecycles, and leading quality initiatives with AWS services.

Lead Platform Engineering to architect, deploy, and manage secure, scalable AWS cloud infrastructure using IaC, CI/CD, monitoring, automation, and container platforms; enforce AWS security governance; mentor engineers and collaborate on solution design.

Design, develop, and maintain scalable analytics solutions on the Looker BI Platform, focusing on LookML modeling and collaboration with data engineers and stakeholders.

The Data Modeler designs and maintains the Common Data Model and source-to-target mappings for healthcare data assets, working closely with engineers and clinical informaticists to ensure accuracy and integrity in data representation.