Top Tech Jobs & Startup Jobs

Architects and manages cloud-native AI infrastructure, containerized workloads, serverless environments, and automated CI/CD pipelines. Builds Terraform-based infrastructure, implements observability, security controls, compliance automation, and cost optimization. Leads client discovery workshops, technical demonstrations, requirements gathering, cloud adoption roadmaps, and enterprise delivery while communicating complex architectures to stakeholders.

Leads enterprise AWS cloud architecture, implementation, migration, modernization, and Generative AI delivery. Builds secure cloud-native systems using Infrastructure as Code, containers, serverless services, CI/CD, and AWS AI platforms. Serves as a client-facing technical leader for executive stakeholders, develops proofs of concept, drives AWS adoption and account growth, and mentors engineers while building reusable cloud delivery practices.

Lead enterprise delivery of Databricks-based data, analytics, and Generative AI solutions. Design production data pipelines, lakehouse architectures, RAG applications, ML platforms, and cloud-native systems. Drive legacy data migrations to Databricks, advise executive client stakeholders, identify platform expansion opportunities, and mentor engineering and consulting teams. The role combines hands-on engineering, solution architecture, customer engagement, and technical practice development.

Lead enterprise AWS consulting engagements from architecture through deployment. Design resilient cloud-native, serverless, and containerized solutions; migrate legacy infrastructure; and deliver Generative AI and machine learning workloads using AWS services. Partner with executive stakeholders, build proofs of concept, drive cloud adoption and account growth, mentor engineers and architects, and develop reusable Terraform modules, Well-Architected Review frameworks, and delivery best practices.

Lead enterprise delivery of Databricks-based data, machine learning, and Generative AI solutions. Design production data pipelines, analytics engines, RAG applications, and ML platforms; migrate legacy data estates to the Lakehouse; and advise executive client stakeholders. Drive platform adoption, identify expansion opportunities, mentor technical teams, and develop reusable engineering accelerators. The role combines hands-on architecture, engineering, consulting, customer engagement, and technical practice building.

Design and evolve modular game engines, visual templates, UI systems, and gameplay frameworks for interactive learning modules. Responsibilities include abstracting graphics and mechanics into configurable systems, establishing UI/UX and visual standards, defining asset pipeline specifications, conducting design and usability reviews, advising clients, and documenting style guides and technical configuration parameters.

Build and optimize Databricks Lakehouse architectures and scalable ETL/ELT pipelines using Spark and Delta Lake across AWS, Azure, and GCP. Tune performance and cloud costs, integrate MLflow for AI model operationalization, and implement CI/CD and Infrastructure-as-Code deployments. Enforce governance, security, and compliance through Unity Catalog. Partner with architects, data scientists, engineers, and clients to deliver production-ready AI solutions and documentation.

Build responsive React frontends and secure, scalable NodeJS and Express backends for cloud-native client applications. Integrate structured and unstructured data across AWS services, implement search and ETL pipelines, optimize performance, and contribute to architecture, APIs, testing, code reviews, and shared components. Collaborate in Agile teams, work directly with clients, gather requirements, demo solutions, and ensure delivery meets business goals.

Build and optimize cloud-agnostic Databricks Lakehouse architectures, scalable ETL/ELT pipelines, and MLOps frameworks across AWS, Azure, and GCP. Tune Spark workloads, automate deployments with CI/CD and Infrastructure-as-Code, and implement monitoring, data quality, governance, security, and compliance controls. Partner with data scientists, architects, ML engineers, and client stakeholders to productionize AI/ML models and deliver enterprise data solutions.

Design and optimize Databricks Lakehouse architectures and scalable ETL/ELT pipelines across AWS, Azure, and GCP. Build Spark and Delta Lake workflows for structured and unstructured data, tune performance and cloud costs, and integrate MLflow for AI model operationalization. Implement CI/CD and infrastructure-as-code deployments, enforce governance and security through Unity Catalog, and collaborate with client leaders to deliver production-ready data and AI solutions.