Top Tech Jobs & Startup Jobs

Owns production cloud infrastructure for AI systems, including Kubernetes clusters, infrastructure as code, CI/CD pipelines, observability, incident response, security hardening, cost management, and capacity planning. The role supports AI inference workloads across cloud environments, maintains internal tooling and documentation, and collaborates directly with developers, QA, and clients. Candidates need strong production DevOps or SRE experience, cloud expertise, infrastructure automation skills, and advanced English communication.

Create and optimize AI-assisted marketing content, social media assets, website materials, and campaigns. Improve GEO, AEO, SEO, and AI search visibility; monitor competitors and content gaps; build marketing reports; analyze KPIs; automate workflows; and support website updates. The role requires strong marketing judgment, creativity, independent project ownership, and effective collaboration with marketing, sales, and leadership teams in a remote environment.

Owns the full data science workflow from framing business questions and selecting methods to modeling, evaluation, error analysis, and handoff. Builds supervised, unsupervised, and deep learning models; adapts pretrained models; designs experiments; validates uncertainty; and works directly in client environments. Requires strong Python, statistics, PyTorch, cloud, and model evaluation expertise, plus the ability to communicate technical trade-offs to clients.

Build and ship production software in client technology stacks, including APIs, services, data models, interfaces, automated tests, CI/CD, and failure handling. Use AI coding agents daily while reviewing all generated code. Work with relational and non-relational databases, third-party integrations, cloud deployments, infrastructure as code, and compliance requirements. Collaborate directly with clients in English and deliver maintainable, tested software end to end.

Owns end-to-end delivery of production software and AI systems inside client environments, from discovery and design through release, verification, and incident response. The engineer works independently, leads client conversations, manages ambiguity, builds reproducible systems with AI coding agents, and deploys using cloud infrastructure, containers, CI/CD, and infrastructure as code. The role requires strong production ownership, client-facing communication, and experience delivering under constraints such as SOC 2 or HIPAA.

Build and operate production data infrastructure, including batch and streaming pipelines, warehouses and lakehouses, retrieval systems, and data-quality controls. Design for schema evolution, reliability, cost, security, compliance, and observability using cloud platforms and modern orchestration tools. Partner directly with clients, explain technical trade-offs, and deploy containerized systems with CI/CD and infrastructure as code. Support AI applications through embedding, indexing, and retrieval pipelines.

Lead end-to-end software development projects from planning through delivery. Manage schedules, budgets, risks, vendors, resources, documentation, and stakeholder communications across multiple concurrent engagements. Facilitate Agile ceremonies using Scrum and Kanban, coach cross-functional teams, and apply AI tools to improve reporting, documentation, automation, and risk identification.

The Business Analyst will lead software development initiatives, manage project backlogs, analyze requirements, and ensure project delivery within Agile frameworks.