Jobs at CapTech

Own and evolve enterprise SaaS and cloud platforms, including configuration, integrations, access models, automation, and security controls. Administer the Microsoft ecosystem and multi-cloud environments, design SSO integrations using SAML and OIDC, and lead provisioning, auditing, and workflow automation with PowerShell, APIs, and AI tools. Partner with IT, Security, and business teams on governance, least privilege, change management, documentation, and platform roadmaps.

Leads end-to-end product and digital experience design for client projects, including research, personas, journey maps, information architecture, wireframes, visual designs, prototypes, usability testing, and developer handoff. Presents design rationale to clients, mentors junior designers, manages design quality, supports client growth, advances CX methodologies, and promotes accessible, multi-channel experiences. Uses AI-powered design tools and collaborates with researchers, strategists, developers, project managers, and clients.

Builds rapid AI demos, prototypes, and reusable client solutions; presents technical work and business value to executives; contributes to internal AI platforms, features, deployments, and security; leads employee enablement sessions; coaches colleagues on AI and agentic coding tools; and evaluates emerging models and technologies.

Designs and leads scalable AI/ML architectures for clients across cloud platforms, including data pipelines, model development, deployment, monitoring, and governance. Advises stakeholders on AI strategy, leads discovery workshops, oversees delivery, establishes AgenticOps practices, supports presales, and develops reusable AI offerings. The role also promotes responsible AI, mentors teams, and contributes to thought leadership and go-to-market initiatives.

The Lead Machine Learning/Data Science Engineer at CapTech designs and deploys machine learning solutions, providing technical leadership and collaborating with teams to meet client needs using large datasets and cloud platforms.

The Machine Learning Engineer designs and implements data-driven solutions, builds scalable ML systems, and collaborates with clients to meet business needs.

Lead data strategy and delivery for clients: translate business needs into data architectures, assess and recommend data management technologies, design governance and quality frameworks, guide integrations and real-time data solutions, mentor teams, and support business development and solutioning.

Lead design and delivery of cloud data pipelines and architectures, advise clients on best practices, implement ETL/orchestration, work with product owners to meet requirements, provide technical leadership and mentor engineers, and maintain scalable data warehouse and lake solutions across cloud platforms.

Design and lead implementation of modern data architectures across cloud and on-prem systems. Assess technologies, improve data integration, quality, governance, and delivery; guide engineering teams, advise executive stakeholders, and support business development and practice growth.

Design, build, and maintain cloud-based data pipelines and architectures on AWS, Azure, or GCP. Advise clients on cloud data solutions, implement production data products, collaborate with stakeholders, and evaluate architectural trade-offs to meet business needs.

Design and recommend end-to-end data architectures to improve data integration, quality, and delivery. Assess current and future-state data platforms, guide cloud and streaming implementations, mentor staff, collaborate with stakeholders, and support business development to estimate and present solutions.