Top Tech Jobs & Startup Jobs

Design, build, and productionize AI/ML solutions including deep learning and generative models. Build scalable data and MLOps/LLMOps pipelines, deploy models to cloud/HPC/edge, preprocess large datasets, perform research and optimization, and collaborate with business and technical stakeholders to deliver production-ready outcomes and justify model value.

Advise clients on AI and data strategy, build value cases and roadmaps, shape AI platforms and operating models, embed Responsible AI, lead large-scale delivery and stakeholder engagement, and tie AI initiatives to measurable business outcomes.

Resolve incidents and problems across business system components to maintain operational stability. Manage and implement Requests for Change, update knowledge base articles, monitor system performance, collaborate with vendors and internal service teams, mentor junior staff, and contribute to process improvements and continuous learning in workplace technology solutions.

Design, build, and deploy scalable AI/ML solutions (including deep learning, generative AI, and LLMs). Develop models, data pipelines, and MLOps/DevOps for training and production, work with large-scale datasets and HPC/edge environments, perform R&D, and collaborate with business and technical stakeholders to deliver production-ready systems.

Technical lead for the Accenture LearnVantage product: define development workflows and architecture, build and review critical backend components, mentor engineers, guide multiple squads, and champion AI coding tools and modern testing/CI practices.

Lead design and delivery of reusable, cloud-native Agentic DevOps frameworks for generative AI agents. Architect CI/CD, orchestration, monitoring, and production-readiness across AWS/Azure/GCP. Manage and mentor cross-functional DevOps and AI teams, ensure enterprise security, reliability, and compliance, and enable client-specific deployments and onboarding.

Embed with client teams to design, deploy, and scale production AI platforms end-to-end. Deliver reliable, measurable business outcomes through rapid prototyping, production deployments, governance, CI/CD, IAC, and stakeholder engagement. Build reusable patterns and enable client ownership while driving AI adoption and ROI.

Atuar como ponte entre negócio e engenharia de dados, traduzindo demandas em requisitos analíticos. Desenvolver dashboards executivos, modelos analíticos e automatizar pipelines ETL/ELT. Trabalhar com grandes volumes e múltiplas fontes, garantindo qualidade, governança e consistência dos dados e indicadores.

Desenvolver, manter e otimizar pipelines de dados em nuvem (principalmente GCP), usando Databricks, BigQuery, Dataflow/Beam, Composer/Airflow e DBT. Garantir qualidade, governança e integração entre bancos (Oracle, Sybase, SQL Server, MySQL), executar análises SQL avançadas, monitorar performance e colaborar com times de engenharia, ciência de dados e analytics para escalar e modernizar a arquitetura de dados.

Design, build, and operate scalable Databricks/Azure Lakehouse pipelines including ELT/streaming, Delta optimization, Unity Catalog governance, CI/CD, MLflow, and data integrations to deliver production datasets for BI/ML/GenAI. Serve as SME, lead and mentor team, and drive cross-team technical decisions.