Lead client-embedded AI workstreams, design and deploy scalable AI solutions, manage multidisciplinary teams, and drive responsible AI practices.
Compensation
The salary range for this job is:
New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $150,700 to $251,200
Bay Area California offices – $157,100 to $261,600
All other offices locations in the US, including Sacramento – $125,500 to $230,200
Responsibilities
Lead client-embedded AI workstreams from opportunity identification to value measurement
Redesign client processes for human-AI collaboration
Manage lean multidisciplinary teams
Build trust with stakeholders and lead product delivery
Define solution architecture and guide development of agentic workflows
Join Our Network of DevOps Professionals! We are looking for consultants who have experience with designing, automating, and supporting scalable cloud infrastructure and containerized environments.
Locations (4)
New York City, New York, United States
Washington, D.C., United States
Boston
Atlanta
Compensation
Compensation commensurate with your qualifications, experience, and other factors including geographic location, market and operational factors.
Responsibilities
Design, deploy, and manage production Kubernetes environments.
Build and maintain reusable Terraform modules for automated infrastructure provisioning.
Enterprise Data Engineer
UTHealth (University of Texas Health Science Center at Houston) · Posted Nov 14, 2026
Design, develop, and operate enterprise data engineering solutions using Microsoft Fabric and related technologies to support analytics and AI use cases.
Responsibilities
Design and implement Bronze, Silver, and Gold data layers
Configure and maintain Fabric workspaces, Lakehouse/Warehouse components, OneLake patterns, pipelines, notebooks/SQL transformations, deployment pipelines, monitoring, and environment promotion
Build source ingestion and integration patterns for PeopleSoft, Oracle Fusion, Epic and other approved sources
Lead the platform track of a mission‑application modernization program for a Department of War customer, managing three scrum teams and driving delivery of platform releases.
Responsibilities
Serve as primary contact for platform stakeholders
Mid-Level DevOps Engineer (AWS) – LATAM. Responsable de colaborar con equipos de desarrollo, infraestructura y QA para automatizar procesos, administrar recursos en la nube, monitorear aplicaciones y contribuir a la estabilidad operativa de los entornos de desarrollo, pruebas y producción.
Locations (3)
Colombia
Mexico
Chile
Responsibilities
Administrar, configurar y mantener infraestructura en Amazon Web Services (AWS)
Implementar y gestionar servicios AWS como EC2, S3, IAM, VPC, RDS y CloudWatch
Participar en el diseño e implementación de infraestructuras escalables, seguras y altamente disponibles
Automatizar la creación, configuración y administración de infraestructura utilizando Terraform o AWS CloudFormation
Desarrollar y mantener scripts de automatización utilizando Bash o Python
Diseñar arquitecturas distribuidas, definir estándares de desarrollo backend, diseñar APIs, implementar estrategias de escalabilidad, definir patrones de diseño, gestionar bases de datos, diseñar mecanismos de seguridad, asegurar monitoreo, logging y observabilidad, colaborar en pipelines CI/CD.
Locations (2)
CDMX, Mexico
Aguascalientes, Aguascalientes, Mexico
Compensation
Capgemini ofrece una compensación competitiva y beneficios superiores a los de Ley.
Systems Engineer on the Experiments & Integration team responsible for rapid response to simulation and emulation requests, performance measurement, and reusable asset creation.
Compensation
The base salary range for this role is Mid: $160,000-$220,000, Senior: $220,000–$270,000, Principal: $270,000-$350,000.
Responsibilities
Serve as the first responder for simulation and emulation requests from hardware, software, and customer teams
Run quick experiments and demos, such as getting a new LLM running on the emulator, profiling where time goes, or trying a configuration a stakeholder wants to see
Measure and explain performance using counters, traces, and end-to-end timing, reported along with their limits and their drivers
Help other teams build on the simulators and the emulation setup when they need integration support
Convert each investigation into a reusable asset, such as a calibrated model, a repeatable experiment, or a regression test
Requirements
Nice to have: hardware emulators Cadence Palladium
Build the layer that lets AI coding agents do real work on our simulators, focusing on platform engineering with a verification mindset.
Compensation
The base salary range for this role is Mid: $160,000-$220,000, Senior: $220,000–$270,000, Principal: $270,000-$350,000.
Responsibilities
Design and build the MCP servers and APIs that let AI coding agents drive our simulators end to end
Make the simulators legible to agents and people alike through clear CLI and API design
Build agent workflows for simulator development in which an agent implements or extends a hardware command's functional, dependency, cost, and cycle models and lands it with test evidence
Partner with the model architecture engineer to automate new-model bring-up from model specification to simulator coverage
Build CI guardrails for agent-produced changes, including golden-reference generation, static analysis, known-good comparisons, and provenance on every result
Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
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