Why Cast AI?

Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production.

The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation.

Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS.

Global team, diverse perspectives
We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead. 

Unicorn momentum
In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started.

Join us as we build the future of autonomous infrastructure.

This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, and Ukraine.

About the role

You'll join one of several teams building the low-level systems behind CAST AI's multi-cloud automation platform. The work sits at the intersection of Kubernetes, cloud infrastructure, and Linux.

Depending on your strengths, you'll work in one of these areas:

• Cluster and node lifecycle - custom node bootstrapping across AWS, GCP, and Azure. Controllers and operators managing full node lifecycle. Bridging the gap between autoscaler decisions and running VMs - including working around limitations of managed Kubernetes platforms like EKS, GKE, and AKS.
• Cross-cloud provisioning - orchestrating infrastructure across regions and clouds. Workflow orchestration, provisioning integrations, networking and identity across cloud boundaries.
• Live container migration - zero-downtime relocation of running containers using CRIU checkpoint/restore, custom CRI-O and runc forks, and forked cloud CNI plugins. Memory page transfer, TCP session migration, process-level checkpoint/restore. Kernel-level Linux engineering applied to Kubernetes.
• Storage optimization - dynamic volume rightsizing, BtrFS compression, custom CSI drivers. Full storage stack from cloud disk APIs through filesystem internals to Kubernetes PV/PVC lifecycle.

Common across all teams: Go, deep Kubernetes, multi-cloud, building beyond what the ecosystem offers.

How we build

We invest heavily in agentic development and AI-powered tooling. Engineers work with code agents and automated workflows daily. We expect you to shape how these tools evolve.

Requirements:

• Strong backend fundamentals and production-grade coding, preferably Go.
• Hands-on Kubernetes internals, cloud infrastructure, or large-scale distributed systems experience.
• Clear English communication, collaborative and self-directed.
• Bias toward action and ownership.

What would make you stand out

• Deep knowledge of EKS, GKE, or AKS internals.
• Low-level Linux experience: process internals, networking (NAT, iptables, conntrack, SDN), filesystems, storage.
• Kubernetes or cloud-native OSS contributions.
• Cloud storage depth - block storage, CSI, volume management, filesystem internals.
• Container runtime experience (CRI-O, runc, containerd) or CRIU.
• Experience with AI coding agents and agentic development workflows.
• Comfort building where there's no playbook.

Responsibilities:

• Design, build, and operate backend services, Kubernetes operators, and controllers in Go across AWS, GCP, and Azure.
• Solve infrastructure-layer problems — networking, scheduling, storage, compute, or container runtime internals.
• Build and maintain high-throughput services (gRPC/REST) and async orchestration workflows.
• Shape public and internal APIs.
• Leverage and improve AI-powered development workflows.
• Participate in design reviews, code reviews, on-call, and customer deep-dives.

What’s in it for you?

• Competitive salary (€6,500 - €9,000 gross, depending on the level of experience)
• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology.
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Annual hackathon to spark new ideas and strengthen team bonds.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

Hiring process

• Screening call with Recruiter
• Hiring Manager interview
• Technical interview (system design)
• Live coding
• Culture Check interview with an executive

*As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
*Please note that Cast AI does not provide any form of visa sponsorship/work permit.

#LI-Remote

Why Kimchi?

Kimchi is the AI platform inside CAST AI. We started by helping companies run LLMs on their own Kubernetes clusters - now we're building the execution layer where agents do real work.

Our Infrastructure today: multi-model inference (MiniMax, Kimi, GLM-5, Nemotron, DeepSeek) with intelligent routing, an OpenAI-compatible API, and deployment flexibility from our GPUs to your VPC. The inference layer is the foundation. What we're hiring for sits on top of it: coding agents, agent runtimes, orchestration systems, and the reliability engineering that makes them actually finish things.

Tech Stack: TypeScript, Go, Kubernetes, AWS/GCP/Azure, MCP, Prometheus/Grafana/Loki, GitLab CI, ArgoCD.

Why harness engineering matters here
OpenAI and Anthropic ship models. They also ship one harness each - the scaffolding that turns a raw model into something that can plan, execute, recover, and complete work. We ship a different kind of harness: one built for cost-conscious, long-horizon autonomy, running on inference infrastructure we control end-to-end.
A decent model with a great harness beats a great model with a bad harness. We've watched this play out. The gap between what today's models can do and what you see them doing is largely a harness gap - and that gap is where we operate.

What you'll build
The ratchet.
Every time our agent makes a mistake, we engineer a solution so it never makes that mistake again. That means hooks that enforce constraints the model "knows" but forgets: pre-commit lint checks, permission gates, context compaction before the window fills. Success is silent, failures are verbose.

Long-horizon execution.
Our harness is built around spec-driven autonomy: meta-prompting, fresh context per task, worktree-per-slice git strategy, automatic replanning, crash recovery, stuck detection. We're implementing Ralph loops - when the model tries to exit, we intercept and reinject the goal into a fresh context. The agent reads state from disk and continues. Multi-session, multi-day work, without context rot.

Planner/executor splits.
Planning with a reasoning model, executing with a fast one, evaluating with a third. Separating generation from evaluation beats self-verification because agents reliably skew positive when grading their own work.

The harness surface.
CLI, TUI, MCP integration, sandboxed execution, telemetry. Our AGENTS.md is short - every line traces to a specific thing that went wrong. TypeScript on the surface, Go where it matters.

Memory and context.
Moving agents off laptops, giving them state that survives across sessions, managing context so information lands where it's actionable. Compaction, tool-call offloading, progressive skill disclosure.

What makes this different (with receipts)
You've seen the pitch: "we route to the best model." Everyone says that. Here's what we actually have:

• GPU infrastructure we own. Not just an API reseller. From GPU placement across clouds to the inference endpoint your agent calls - we control the cost curve.
• A harness-first thesis. We treat agent failures as configuration problems, not model problems. When we moved from a stock harness to our own, completion rates on internal benchmarks improved by 40%+ on the same model.
• Agents.md that earns every line. No brainstormed rules - every constraint in our system prompt traces to a real failure we saw and fixed.

Requirements:

• You've used AI coding agents in anger. Not demos - real work. You have opinions about Claude Code, Codex, OpenCode, Cursor. You know what it feels like when an agent gets stuck and why.
• Strong TypeScript or Go in production. Comfort moving between them. Our surface is TypeScript; our core is Go.
• You think in harness terms. You read "the agent hallucinated" and your first instinct is to ask what context it was missing, what hook should have caught it, what constraint should exist.
• You drive features end-to-end. Design → build → ship → measure → iterate. We don't have layers that absorb ambiguity for you.

Responsibilities:

• Build and evolve the agent harness - ship hooks, permission gates, and context compaction. Every AGENTS.md constraint traces to a failure you personally diagnosed.
• Own long-horizon execution - multi-session task completion via spec-driven prompting, worktree-per-slice git, Ralph loop recovery, and stuck detection. Completion rate is your metric.
• Architect planner/executor/evaluator pipelines - planning with a reasoning model, execution with a fast one, evaluation with a third. No self-verification.
• Manage agent memory and context - state persistence across sessions, context compaction, tool-call offloading. Zero context rot on multi-day work.
• Own the harness surface - CLI, TUI, MCP integrations, sandboxed execution, telemetry. TypeScript on the surface, Go where it matters.

What success looks like (after 6 months):

• You've shipped at least one major harness feature end-to-end: designed it, built it, measured it, iterated.
• You've added constraints to our AGENTS.md based on failures you personally observed and diagnosed.
• You've improved a measurable reliability metric - completion rate, context efficiency, or cost per successful task.
• You've formed strong opinions about where our harness is load-bearing and where it's dead weight.

What’s in it for you?

• Competitive salary (€6,500 - €9,000 gross, depending on the level of experience).
• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Annual hackathon to spark new ideas and strengthen team bonds.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, and Ukraine.

*As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
*Please note that Cast AI does not provide any form of visa sponsorship/work permit.

#LI-Remote

Why Cast AI?

Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production.

The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation.

Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS.

Global team, diverse perspectives
We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead. 

Unicorn momentum
In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started.

Join us as we build the future of autonomous infrastructure.

This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, and Ukraine.

We are hiring across multiple teams!

As a Senior Software Engineer, you will have the opportunity to work on different key features of our product. We are currently hiring Senior Software Engineers for the following teams:

- Workload Optimization - Automates workload resource management by dynamically adjusting resource allocations, helping developers significantly reduce costs and improve application reliability.

- Karpenter - The Karpenter team powers the integration between Karpenter and Cast AI, bringing enterprise capabilities to the most popular open source Kubernetes autoscaler. We enhance Karpenter with advanced features that improve application reliability and performance while optimizing costs. By joining the team, you’ll bridge open source innovation with enterprise requirements, directly impacting how organizations run Karpenter at scale.

- Reporting - Builds a scalable reporting system that ingests millions of rows per second into our time-series databases, providing insights into cost savings, workload efficiencies, and Cast AI automation impact.

- Pricing - Drives the synchronization of public and customer cloud resources, availability, and dynamic pricing across all major cloud providers. Empowers autoscaling by leveraging discounts, commitments, and cross-cluster tracking to maximize savings. Provides a reliable source of truth for node pricing, resources, components, discounts, and commitments.

- Autoscaler - Automates Kubernetes node autoscaling to optimize clusters, balance workloads, remove underutilized nodes, and dynamically allocate capacity in real-time, thereby reducing cluster costs by half.

- Identity -  Builds and maintains the trust and access foundation for the entire platform, ensuring every user, service, and workload authenticates and interacts securely and seamlessly at scale.

- Billy -  Powers the critical day-2 operations layer of the platform - from billing and audit trails to notifications and feature flags - ensuring the platform runs reliably, transparently, and at scale for every customer, every day.

Here are some of the tools we use daily:

• Programming Languages: Go
• Cloud & Orchestration: Kubernetes, AWS, GCP, Azure
• Databases & Storage: PostgreSQL, Cloud Object Storage
• Messaging & APIs: GCP Pub/Sub, gRPC for internal communication, REST for public APIs
• Observability: Prometheus, Grafana, Loki, Tempo
• CI/CD & GitOps: GitLab CI with ArgoCD.

Requirements:

• Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language.
• Deep hands-on experience with cloud platforms (AWS, GCP, or Azure) - including real understanding of how compute, networking, and storage work under the hood.
• Understanding of Kubernetes internals - autoscaling and networking.
• You've personally driven a complex project end-to-end.
• Strong debugging, optimization, and performance-tuning skills - including query profiling, index design, and database performance tuning beyond ORM usage.
• You've run observability tooling (Prometheus, Grafana, OpenTelemetry) in production.
• CI/CD and DevOps practices experience.
• Strong English skills, both verbal and written.
• Startup mindset: adaptable, proactive, and comfortable with ambiguity.

Responsibilities:

• Design and build distributed systems that operate Kubernetes infrastructure autonomously at scale.
• Write production Go services that interact with AWS, GCP, and Azure APIs for real-time cloud resource management.
• Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1-4 weeks).
• Debug complex production issues across cloud providers, Kubernetes clusters, and distributed services.
• Collaborate with product and other engineering teams to solve problems that don't have textbook solutions.
• Work with time-series data, cloud provider APIs, and Kubernetes control plane internals.

What’s in it for you?

• Competitive salary (€6,500 - €9,000 gross, depending on the level of experience)
• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology.
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Annual hackathon to spark new ideas and strengthen team bonds.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

Hiring process

• Screening call with Recruiter
• Hiring Manager interview
• Technical interview (system design)
• Live coding
• Culture Check interview with an executive

*As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
*Please note that Cast AI does not provide any form of visa sponsorship/work permit.

#LI-Remote

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.

We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount. 

Our interview process involves several technical interviews and we aim to complete them within 1 week. 

What You’ll Do

• Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
• Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
• Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
• Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have

• Proven experience in backend development: TS/Node (required)
• Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
• Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
• Preferred: Experience with Docker and containerized deployments
• Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer

• A dynamic environment where your contributions shape the company and its products
• A team that values innovation, intuition, and drive
• Autonomy, fostering focus and creativity
• The opportunity to have a significant impact in a revolutionary industry
• Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
• The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
• An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Let's start with the role

At Kaizen, we strive to harness the power of modern AI algorithms to continuously improve our product and business. Kaizen’s AI department consists of product, platform and research teams and lies at the core of that mission. We develop AI products for various applications, ranging from detection of fraudulent activity to personalized gaming recommendations and from AI-powered co-pilots to CRM optimizations. 

We structure our teams to be self-driven, autonomous, and cross-functional. Within these teams, you will have the opportunity to work with Data Scientists, Machine Learning Engineers, Data Engineers, Data Analysts, Product Owners and Agile Delivery Leads.

As a Senior Machine Learning Software Engineer, you will focus on delivering robust and scalable Machine Learning pipelines and you will support the operationalization of Machine Learning models. 

• Collaborate closely with data scientists in order to deliver production-ready model training pipelines;
• Design scalable solutions in a distributed environment;
• Design scalable inference pipelines and architectures;
• Implement model diagnostics such as evaluation, monitoring flows etc.;
• Automate model deployment, enable REST API model endpoints;
• Develop scalable model serving flows;
• Work on cluster optimization and scalability;
• Develop and maintain internal tools and libraries;
• Write CI/CD/CT pipelines.

What you’ll bring

• Extensive experience in software development using Python in large scale, high-performance production environment;
• Significant hands-on experience in designing ML software systems;
• Significant experience with cloud environments like Microsoft Azure or AWS;
• Solid understanding of:
• The ML project lifecycle;
• MLOps concepts and tools such as MLflow or Kubeflow;
• ML algorithms and models.

• Hands-on experience with Spark and PySpark;
• Excellent problem solving and communication skills.

#Machine Learning (ML) #MLOps #AIOps #Software Engineering

Kaizen Gaming Perks

• 🕑 Hybrid way of working;
• 🏃 A buddy will support you with your onboarding;
• 💸 Competitive pay & bonus scheme;
• ⭐Developmental 360° feedback framework;
• 💰 Monthly meal allowance;
• 👩‍⚕️ Private health insurance for you and your family;
• 📚 Unlimited access to Udemy & continuous training;
• 👨‍👩‍👧‍👦 Family Support.
• #LI-Hybrid
• #LI-EL1

Let's start with the role

At Kaizen, we strive to harness the power of modern AI algorithms to continuously improve our product and business. Kaizen’s AI department consists of product, platform and research teams and lies at the core of that mission. We develop AI products for various applications, ranging from detection of fraudulent activity to personalized gaming recommendations and from AI-powered co-pilots to CRM optimizations. 

We structure our teams to be self-driven, autonomous, and cross-functional. Within these teams, you will have the opportunity to work with Data Scientists, Machine Learning Engineers, Data Engineers, Data Analysts, Product Owners and Agile Delivery Leads.

As a Senior Machine Learning Software Engineer, you will focus on delivering robust and scalable Machine Learning pipelines and you will support the operationalization of Machine Learning models. 

• Collaborate closely with data scientists in order to deliver production-ready model training pipelines;
• Design scalable solutions in a distributed environment;
• Design scalable inference pipelines and architectures;
• Implement model diagnostics such as evaluation, monitoring flows etc.;
• Automate model deployment, enable REST API model endpoints;
• Develop scalable model serving flows;
• Work on cluster optimization and scalability;
• Develop and maintain internal tools and libraries;
• Write CI/CD/CT pipelines.

What you’ll bring

• Extensive experience in software development using Python in large scale, high-performance production environment;
• Significant hands-on experience in designing ML software systems;
• Significant experience with cloud environments like Microsoft Azure or AWS;
• Solid understanding of:
• The ML project lifecycle;
• MLOps concepts and tools such as MLflow or Kubeflow;
• ML algorithms and models.

• Hands-on experience with Spark and PySpark;
• Excellent problem solving and communication skills.

#Machine Learning (ML) #MLOps #AIOps #Software Engineering

Kaizen Gaming Perks

• 🕑 Hybrid way of working;
• 🏃 A buddy will support you with your onboarding;
• 💸 Competitive pay & bonus scheme;
• ⭐Developmental 360° feedback framework;
• 💰 Monthly meal allowance;
• 👩‍⚕️ Private health insurance for you and your family;
• 📚 Unlimited access to Udemy & continuous training;
• 👨‍👩‍👧‍👦 Family Support.
• #LI-Hybrid
• #LI-EL1

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.

We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount. 

Our interview process involves several technical interviews and we aim to complete them within 1 week. 

What You’ll Do

• Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
• Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
• Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
• Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have

• Proven experience in backend development: TS/Node (required)
• Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
• Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
• Preferred: Experience with Docker and containerized deployments
• Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer

• A dynamic environment where your contributions shape the company and its products
• A team that values innovation, intuition, and drive
• Autonomy, fostering focus and creativity
• The opportunity to have a significant impact in a revolutionary industry
• Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
• The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
• An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

How You'll Make an Impact: 

As a Senior DevOps Engineer at Cloudbeds, your goal is to constantly improve and scale our SaaS platform to deliver an exceptional experience to hoteliers and their guests worldwide. You'll own the creation, monitoring, automation, and support of our cloud infrastructure and delivery pipelines — enabling product teams to ship high-quality software with speed and confidence. Working within a bottom-up culture that values healthy debate and collaborative problem-solving, you'll have real influence over architecture decisions and the opportunity to shape how we scale infrastructure for one of the fastest-growing hospitality technology platforms in the world.

Our Infrastructure Team: 

Our Infrastructure team is made up of engineers who take genuine pride in their craft, owning projects end-to-end and holding themselves to a high bar. We're passionate about technology and constantly pushing to improve our stack, not just maintain it. If you thrive in an environment where attention to detail matters, great communication is a given, and you're comfortable challenging the status quo to make things better, you'll feel right at home here.

What You Bring to the Team:

• Architect, improve, and scale Cloudbeds' cloud infrastructure on AWS, with a focus on reliability, security, and performance
• Build and evolve our Kubernetes (EKS) platform, driving adoption of containerization best practices across engineering teams
• Automate infrastructure provisioning and configuration using infrastructure-as-code tools like Terraform
• Design, build, and maintain CI/CD pipelines (GitHub Actions, ArgoCD) that enable fast, reliable software delivery
• Partner with product and engineering teams to drive projects to production, sharing DevOps expertise and ensuring strong environment configuration from the infrastructure side
• Maintain and improve monitoring, logging, and alerting systems to ensure platform health and rapid incident response
• Participate in on-call rotation to support production environment stability.

What Sets You Up for Success:

• 5+ years of experience as a DevOps Engineer working hands-on with AWS (networking, compute, storage, databases, queues, cache, permissions).
• 5+ years of strong Kubernetes and Docker experience, including implementing and scaling EKS platforms at production scale.
• Deep expertise with Terraform for infrastructure-as-code and configuration management.
• Proven experience building and supporting CI/CD pipelines using GitHub Actions and ArgoCD.
• Strong knowledge of monitoring and observability tools such as Datadog, Prometheus, Loki, or AWS CloudWatch.
• Working knowledge of web application servers (NGINX, Ingress controllers), databases (MySQL, PostgreSQL, Aurora), caching (Redis, Memcached), and queue technologies (SQS).
• Ability to write Bash and/or Python scripts to automate operational tasks.
• Strong Linux system administration skills and solid networking fundamentals.
• Excellent written and verbal English communication skills; comfortable working asynchronously across a globally distributed remote team.

#LI-REMOTE #LI-IK1

We are looking for a Distributed Systems Engineer with experience in building high-performing, scalable, enterprise-grade applications. You will be responsible for building API interfaces (for customers, UI team etc). You will be responsible for building a high performance queuing/storage engine. You will collaborate with UI, connectivity and DevOps teams to come up with elegant solutions to complex problems. You will work in a polyglot environment where you can learn new languages and technologies whilst working with an enthusiastic team.

Responsibilities

• Responsibilities include designing and developing high-volume, low-latency applications for mission-critical systems and delivering high-availability and performance

• Contribute in all phases of the development lifecycle

• Write well designed, testable, efficient code

• Evaluate and propose improvements to existing system

Requirements

• 5+ years of industry experience

• Experience building and shipping large-scale, reliable, highly distributed systems

• Systems-level programming experience, especially in C, Go, Rust

• Expertise in L2, L3, and/or L4 networking protocols

• Good understanding of Linux networking and security

• Experience building on top of Linux kernel networking primitives – netfilter, nftables, eBPF, tc, network namespaces, etc

• Experience with large-scale distributed data pipelines, from data structuring to efficient querying to data analysis

• Experience of working with public cloud infrastructure providers (AWS/Azure/Google Cloud)

• Understanding of Kubernetes concepts

• Excellent debugging and optimization skills

• Understanding at the protocol level, including the differences between what the specs say, and what actually happens on the Internet

• Contributions to open source projects is a plus

• Excited by the idea of optimizing complex solutions to general problems

• Attention to detail and ability to solve complex customer problems

• Own solutions end-to-end and driving the design, development, and deployment process

• Able to work across teams and level common, sustainable solutions

Responsibilities

We're looking for a hands-on Platform/Observability Engineer to join our infrastructure team. You'll own and evolve our observability stack - from logging pipelines and tracing to metrics and alerting - across a multi-datacenter, Kubernetes-based environment. This is a production-first role: you'll be expected to ship, iterate, and improve systems under real delivery pressure, not just design them on paper.
You'll work closely with other infra and product engineering teams to improve observability coverage, reduce operational toil, and help the broader organization adopt better practices.
Tech Stack Highlights: OpenTelemetry · Kafka · Vector · VictoriaMetrics · EKS · Kubernetes · Logging pipelines · Distributed tracing · SPM· AWS

• Designing, deploying, and maintaining production observability stacks (logs, metrics, traces)

• Scaling observability infrastructure across multiple data centers and Kubernetes clusters

• Owning logging pipeline architecture and refactoring efforts

• Improving distributed tracing coverage and driving adoption across engineering teams

• Managing EKS upgrades, node exporters, agents, and collectors

• Automating operational tasks to reduce toil and improve system stability

• Contributing to compliance and audit readiness (access controls, data handling, pipeline integrity)

• Evaluating and adopting new observability tooling - knowing what's worth pursuing and what isn't

Requirements

Core technical experience:

• 8+ years of industry experience

• Solid hands-on production experience with observability systems

• Strong plus - familiarity with OpenTelemetry, Kafka, Vector, and VictoriaMetrics (vmagent, alerting rules)

• Experience with logging pipelines: design, deployment, and refactoring

• Understanding of distributed tracing and SPM (Service Performance Monitoring) built on top of tracing

• Experience with Kubernetes cluster lifecycle management (EKS preferred)

• Practical knowledge of storage trade-offs for observability data at scale

Nice to have  

• Experience using AI to automate infrastructure or observability tasks (e.g., automated RCA, PR generation, deployment workflows)

• Familiarity with AI-assisted tooling selection and workflow integration

• Experience with MCP (custom or open-source implementations)

• Background in cloud account or environment migrations

• Experience preparing infrastructure for compliance/audit processes

• Understanding network architecture, troubleshooting and incident resolution skills in Production environment, writing Post-mortems.

• Experience with containers and Kubernetes (installation and configuration of operators). 

• Basic knowledge of one or more high-level programming languages, such as Python, Golang, Java

Soft Skills / Personal Characteristics

• Good communication and collaboration skills in international technological companies.

• Interest in modern big distributed storage technologies, architectures.

• Good Spoken English to participate in product-related, architectural and technical discussions.

• Proper balance between being hands-on and deeper analytical approaches

(REQ ID: 2640)

What We Do: AI Service Management (AISM):

Aisera offers the world's first AI-driven service experience solution that automates operations and support for IT, Sales and customer service, making businesses and customers successful by offering consumer-like self-service resolutions to users. Aisera fast tracks the digital transformation journey with user and service behavioral intelligence that drives end-to-end automation of tasks, actions, and business processes. Aisera is a top-tier, VC-funded startup headquartered in Palo Alto, Calif. and a strategic partner with AWS, Microsoft Azure, Google Cloud, ServiceNow and Salesforce.

Aisera has received numerous recognitions, including the following: Forbes AI50; CNBC Upstart 100 Top Startup; Gartner Cool Vendor; Red Herring Top 100 Global Innovator; CIO Innovation Startup Award; CIO Review Top ITSM Solution; Aragon Research Hot Vendor; TiE50 Startup Award; and Silicon Review 50 Most Admired Companies.

The Role: 

Lead AI/ML research and development initiatives while growing as a software engineer. Drive machine learning innovation with strong research acumen while building production-ready ML systems. Partner with AI Systems Tech Lead for technical mentorship and system integration.

Key Responsibilities:

• Lead ML research, experimentation, and development from concept to deployment
• Design and implement novel ML/AI approaches, staying current with cutting-edge research and methodologies
• Architect ML pipelines, training infrastructure, and model evaluation frameworks
• Guide ML engineering decisions including model selection, feature engineering, and optimization strategies
• Translate academic insights into practical applications
• Mentor junior ML engineers and establish ML best practices across the team
• Work closely with AI Systems Tech Leads to ensure delivery of optimized AI systems and services to production
• Enforce data governance and privacy: Follow processes and implement methods that ensure data governance, privacy, and security. 
• Collaborate with cross-functional teams: Work closely with product managers, and other stakeholders to ensure the AI/ML solutions align with the organization's goals and objectives.
• Communicate effectively: Clearly document your work and effectively communicate your findings, insights, and recommendations to both technical and non-technical stakeholders, fostering a collaborative and informed environment.

Required Expertise:

• 5+ years in ML engineering with demonstrated advanced development or research capabilities (innovative projects, publications, theses)
• Advanced degree in AI/ML or related subjects with relevant undergraduate degree
• Deep understanding of ML fundamentals: deep learning, statistical modeling, optimization, and evaluation methodologies
• Strong Python skills with ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face)
• Experience with ML experiment tracking, model versioning, and reproducible research practices
• Ability to translate research papers into working implementations
• At least a year of leadership experience driving technical ML initiatives for a small team
• Solid foundation in software development practices (testing, version control, code review)

Growth Opportunities:

• Opportunity to lead both research direction and technical implementation
• Direct involvement in productionizing cutting-edge ML research
• Accelerated software engineering development 

Preferred (in order):

• Background in NLP 
• Experience with distributed training, MLOps, and cloud ML platforms
• Track record of research publications or open-source ML contributions
• Enterprise SaaS experience 

This role is in a Product-building AI/ML team. This is a Greece-based, full-time, employee-status, fully remote position. 

Aisera is Global and our success draws upon the diverse viewpoints, skills and experiences of our employees. We are proud to be an equal opportunity employer and are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or veteran status.

Senior Software Engineer - Conversational AI & Automation

Aisera is a leading provider of AI Copilot solutions, utilizing AiseraGPT and Generative AI to facilitate business transformation and drive revenue growth through a self-service model. Aisera’s AI Copilot uses industry and domain-specific LLMs to deliver human-like experiences and auto-remediate requests through AI workflows. With 400+ integrations and 1200+ prebuilt workflows, customers achieve 75%+ automation and 90% cost reduction.

Aisera has received numerous recognitions, including the following: FastCompany Best Workplaces for Innovators; Inc 5000 Award for Fastest Growth; Forbes AI50; EY Entrepreneur of the Year 2023; CNBC Upstart 100 Top Startup; Gartner Cool Vendor; Red Herring Top 100 Global Innovator; CIO Innovation Startup Award; CIO Review Top ITSM Solution; and Silicon Review 50 Most Admired Companies. 

Our seasoned founding team has led companies through several prior successful startups and acquisitions. We give our employees a lot of responsibility and ownership of their work, and we hire people from a very wide range of backgrounds and experience. Our team members operate with a high degree of empathy for our customers and each other.

Join our dynamic and fast-paced team and be a part of our journey to revolutionize the industry.

The Role: 

We are looking for a skilled software engineer with strong hands-on experience and the ability to provide technical guidance and direction to team members.

As a Senior engineer, you will play a crucial role in designing, developing, and maintaining our conversation AI & Automation building blocks and features, with a focus on microservices architecture. Your expertise in product development, technical vision and leadership will be valuable in shaping our innovative solutions and enhancing our existing products. 

This role is based out of Athens, Greece (Remote)

Responsibilities:

• Design, build, and deliver scalable and real-time systems with high quality, scalability, and operability in mind.
• Collaborate with product management, data science, and other engineering teams to bring end-to-end solutions with the highest business value to our customers.
• Review and provide feedback on technical designs and code changes to ensure highly available, scalable, maintainable designs and high code quality standards to engineering peers.
• Troubleshoot and resolve complex technical issues that arise in production and provide timely resolutions.
• Proactively identify areas of technical debt and improvement opportunities, and drive solutions or innovation in engineering organization.
• Take operational ownership of the system by using monitoring and observability tools to identify and resolve production issues. 
• Mentor and support team members to raise the technical bar on the team.

Required Qualifications:

• 5+ years hands-on experience with microservices and scalable software development.
• Experience with distributed systems, large-scale data, and the full software lifecycle of modern computer languages (java, python, postgres/mariadb, Redis, Kafka etc).
• Strong understanding of software development principles, design patterns, and best practices.
• Practical experience in database design and integration, including SQL and NoSQL databases.
• Excellent communication and teamwork skills, with the ability to collaborate effectively with team members and stakeholders.
• Bachelor's degree in Computer Science, Software Engineering, or a related field

Preferred Qualifications:

• Experience with cloud platforms (e.g AWS, GCP) is highly desired
• Familiarity with SaaS concepts and experience in developing SaaS-based applications is a plus.
• Domain knowledge experience with ServiceNow, Salesforce, workflow, business process etc.

Aisera is Global and our success draws upon the diverse viewpoints, skills and experiences of our employees. We are proud to be an equal opportunity employer and are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or veteran status.

Aisera is a leading provider of AI Copilot solutions, utilizing AiseraGPT and Generative AI to facilitate business transformation and drive revenue growth through a self-service model. Aisera’s AI Copilot uses industry and domain-specific LLMs to deliver human-like experiencs and auto- remediate requests through AI workflows. With 400+ integrations and 1200+ prebuilt workflows, customers achieve 75%+ automation and 90% cost reduction. Aisera has received numerous recognitions, including Leader in the 2024 Gartner Magic Quadrant™ for Artificial Intelligence Applications in ITSM, FastCompany Best Workplaces for Innovators, Inc 5000 Award for Fastest Growth, Forbes AI50, EY Entrepreneur of the Year 2023, CNBC Upstart 100 Top Startup, Gartner Cool Vendor, Red Herring Top 100 Global Innovator, CIO Innovation Startup Award, CIO Review Top ITSM Solution, and Silicon Review 50 Most Admired Companies.

The Role
Take this opportunity to lead the design and development of advanced AI systems including intelligent agents, conversational interfaces, and retrieval-augmented generation (RAG) architectures and systems. Drive technical strategy and implementation for next-generation AI products.

Responsibilities

• Architect and build scalable agentic AI systems capable of autonomous decision-making and task execution
• Architect, design and optimize dialog agents with natural language understanding, context management, and multi-turn conversation capabilities
• Develop and optimize robust search and retrieval systems for RAG implementations, including vector databases, embedding strategies, and knowledge integration
• Take ownership of complex system design, from proof-of-concept to production deployment
• Establish best practices for AI model integration, prompt engineering, and system reliability
• Collaborate with product teams to translate business requirements into technical AI solutions
• Develop and maintain scalable, efficient data pipelines that automate the ingestion, transformation, and storage of data
• Identify performance bottlenecks and improve systems scalability.

Requirements

• At least 7 years in senior software engineering roles, with 2+ years as tech lead or architect 
• 2+ recent years professional work on AI or Search systems 
• Expertise in vector search, embedding models, or RAG system optimization
• Strong background in distributed systems, APIs, and cloud-native AI infrastructure
• Experience with AI frameworks (LangChain, LlamaIndex, etc.), and vector databases or information retrieval systems (preferably Elastic)
• Solid understanding of software development principles and architectural best practices.
• Professional experience with messaging systems such as Kafka, RabbitMQ, or similar technologies.
• Professional experience with cloud platforms such as AWS, GCP or Azure.
• Proficiency in using Docker, Kubernetes, or similar containerization and orchestration tools.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

Preferred Qualifications (in order):

• Ph.D. in distributed systems, AI systems, or related area
• Familiarity with machine learning concepts and libraries (e.g., Pandas, NumPy, PyTorch).
• Experience with LLM integration, prompt engineering, and AI orchestration frameworks. 

This is a Greece-based, full-time, employee-status, fully remote position.  

Aisera is Global and our success draws upon the diverse viewpoints, skills and experiences of our employees. We are proud to be an equal opportunity employer and are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or veteran status.

Launch Your Tech Career with a Global Investment Bank – Junior SRE/DevOps Engineer (Athens)

Are you a recent Computer Science or Engineering graduate – or someone with technical know-how and a passion for automation, systems, and infrastructure?

Join the mthree Alumni Graduate Programme, designed to give you everything you need to start strong. From expert-led training to an impactful 12-month placement with a world-leading investment bank, this is your launchpad into the world of Site Reliability Engineering and DevOps.

What You’ll Do

• Support critical infrastructure and deployment pipelines for enterprise-grade systems.
• Learn and apply best practices in system reliability, observability, and automation.
• Work with CI/CD tools, containerisation technologies like Docker, and orchestration platforms like Kubernetes.
• Monitor system performance, identify bottlenecks, and help ensure uptime and reliability.
• Troubleshoot incidents in production environments and implement long-term fixes.
• Collaborate with development, QA, and infrastructure teams to improve system resilience and performance.

 What We’re Looking For

• A Bachelor’s degree in Computer Science, Engineering, or a related field (Grade 7/10 or above).
• A basic understanding of system administration, networking, or cloud services (e.g. AWS, Azure, GCP).
• Familiarity with scripting languages such as Python, Bash, or PowerShell.
• An interest in automation, system monitoring, and CI/CD best practices.
• Fluent English communication skills (written and spoken).
• Completed Greek military service, if applicable.
  (Due to the nature of our client commitments in Greece — including long-term placements and time-sensitive onboarding — we require all candidates who are subject to mandatory national service to have either completed or been formally exempted from it prior to joining.)
• Applicants must have the permanent legal right to live and work in Greece at the time of application and on an ongoing basis. Unfortunately, we are unable to provide visa sponsorship now or in the future.

How the Programme Works

1. Apply – Submit your application and complete our online assessment.
2. Interview – Phone/video interview with our Talent Team.
3. Assessment Centre – Join an in-person group session in Athens.
4. Client Interview – Meet and interview with your future team.
5. Train – Attend 8 weeks of paid, expert-led training with mthree Academy.
6. Placement – Begin your 12-month placement with a global investment bank through mthree.
7. Launch – Transition into a permanent role with the client after successful completion.

What You’ll Get

• Paid training delivered by industry professionals.
• A competitive graduate salary, benefits package, and seasonal bonuses (Christmas & Easter).
• Ongoing mentorship, career coaching, and professional development support.
• A clear path to a permanent role with a top-tier investment bank.
• No training bond, hidden fees, or fine print — just a real opportunity.

Diversity and Inclusion at mthree

At mthree, we celebrate diversity and foster an environment where everyone can thrive.
We value inclusion, equality, and the health and well-being of all employees, ensuring our culture supports courageous teamwork, continuous learning, and making an impact.