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Senior Artificial Intelligence Engineer
Key Responsibilities 1. Team Leadership and Technical Direction Lead, mentor, and manage a team of AI Engineerssetting technical direction, reviewing architecture and code, and supporting their day-to-day growth. Act…
AWS DevOps Architect - Python/Kubernetes
Job Title : AWS DevOps Architect Key Responsibilities : - Design and implement endtoend CI/CD pipelines using GitHub, CodeBuild, CodeCommit, CodePipeline and Docker. - Architect, deploy, and manage containerized…
Software Engineer II, Marketplace Optimization
Software Engineer II on Upstart's Marketplace Optimization team, building scalable backend and distributed systems for real-time marketplace decisioning, borrower-investor matching, offer selection, experimentation, and monetization at an AI-driven lending marketplace. Expected stack experience includes modern backend languages such as Ruby, Python, or Kotlin.
Lead Forward Deployed Engineer - AI Transformation
Hands-on technical leadership role in Deloitte Israel's new AI Transformation team: own ambiguous enterprise transformation problems end-to-end, reimagining business processes for an AI-native world and building AI-powered applications, agents, and workflows from architecture through production. Core stack: LLMs, AI agents, backend, distributed systems, cloud.
Python Backend Engineer
Build Python back-end services and REST APIs for a metadata/knowledge platform: source registration, integrations with external APIs, metadata modeling, persistence, and observability. Needs ~4 years of backend experience, strong Python, SQL/NoSQL (incl. graph DBs), cloud and CI/CD. B2B contract, hybrid work in Kraków.
Java Backend Engineer
Java Backend Engineer (Kraków, hybrid, B2B) building back-end services and REST APIs for source registration, metadata management and a Knowledge Platform — including external API integrations, SQL/NoSQL persistence, observability and CI/CD. Pay is 28.4k–31.5k PLN net/month.
Senior Data Engineer
Our data team has expertise across engineering, analysis, architecture, modeling, machine learning, artificial intelligence, and data science. This discipline is responsible for transforming raw data into actionable…
Системный администратор (Астра Облако)
Навыки: Linux, Zabbix. Специализации: Системный администратор. «Астра Облако» — облачный провайдер. Мы создаем Astra Cloud - российскую платформу, для крупного бизнеса госкомпаний, ориентированную на простую…
Senior GCP DevOps Engineer
Role & responsibilities : Own production GKE architecture and lifecycle: clusters, node pools, autoscaling, storage, networking, add-ons, Kubernetes version upgrades, and worker-node patching. - Design and execute low-…
Software Engineer – Cloud Hosting (Python)
Builds and operates the backend services and AWS infrastructure that host UniFi and UISP customer instances in the cloud — provisioning, upgrades, monitoring, backups, and lifecycle management for thousands of hosted environments. Core stack: Python, Linux, Docker, relational databases, networking.
Software Engineering Leader - Campinas/SP
Leads Agibank's engineering teams for the credit journey and decision engines at its Campinas site (on-site): people leadership (1:1s, PDIs), war-room incident response, DORA/SLO/MTTR metrics, technical-debt management, and adopting AI copilots/agents to speed up delivery.
Software Engineering Leader - Campinas/SP
On-site engineering leadership role at Agibank, a Brazilian digital bank, in Campinas/SP: leading development squads, managing people (1:1s, PDIs), overseeing engineering health, technical debt and DevOps/observability practices, and driving adoption of AI tools such as copilots to boost team productivity.
Engineering Manager - SRE
Engineering Manager The Engineering Manager SRE & DRE will lead and develop India-based Site Reliability and Database Reliability Engineers, owning their career growth, performance, wellbeing and team capability while…
Senior AI Security Analyst - Campinas/SP
Agibank is hiring a Senior AI Security Analyst in Campinas, Brazil (hybrid) to act as the technical lead of its AI Security team — governing AI gateway security, LLM/agent security testing, and task automation with n8n — while mentoring engineers and keeping AI initiatives compliant with banking regulations (CMN 4.893, LGPD). Core stack: Python, LLMs/agents, MCP, Promptfoo, n8n, CI/CD, OAuth2/OIDC
M73 - Full Stack Engineer
Full-stack engineer at FPT Asia Pacific building production-grade applications for Singapore government operations, initially an AI-enabled high-volume document processing platform. Day to day: React/TypeScript frontends, Node.js backends and APIs, LLM/OCR integration, CI/CD, security compliance, and production support.
Head of AI Solutions-R&D and Innovation Center
Deloitte R&D and Innovation Center is looking for a Head of AI Solutions . We are looking for a senior, client-facing technology leader to shape, sell, and deliver high-impact AI and agentic-AI solutions for leading…
Senior Director, BSS Engineering & Product
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Director, BSS Engineering & Product based in the United States. As Senior…
Quality Assurance Engineer - Playwright
About Onit We're redefining the future of legal operations through the power of AI. Our cutting-edge platform streamlines enterprise legal management, matter management, spend management and contract lifecycle…
Staff Backend Engineer - Architecture Lead, AWS Serverless
Staff backend engineer at oOh!media (out-of-home advertising) in Sydney, owning a commercial domain for inventory availability and campaign scheduling across the national network. Combines hands-on delivery with architecture leadership, building with Golang or Node.js and AWS serverless, with a focus on data integrity, observability and scalability.
Senior Platform Engineer, MLOps & ML Platform Lead
Staff platform engineer at Commonwealth Bank leading the MLOps/ML platform: evolving platform standards and paved roads, and building reusable infrastructure, training pipelines, model registry and compliant promotion paths so data-science teams can productionise ML at scale, with observability and governance across the lifecycle.