JUTEQ

JUTEQ is an AI-native and cloud-native technology consulting firm helping enterprises in financial services, telecom, and healthcare build intelligent, production-grade systems. We combine the power of GenAI, cloud architecture, and automation to deliver next-generation business tools.

We’re now hiring an experienced QA Engineer to lead quality assurance efforts across our AI agent platform. This is a hands-on role focused on building test plans, validating system behavior, and ensuring a seamless user experience across multi-tenant, AI-powered applications.

What You'll Work On

• Define and execute comprehensive test strategies for our multi-tenant dashboards and AI-driven systems.
• Design and run test cases for complex workflows, including authentication, RBAC, and agent response monitoring.
• Perform both manual and automated testing across web UIs and backend APIs.
• Create regression, smoke, and sanity test suites to support frequent feature releases.
• Collaborate with frontend and backend engineers to identify edge cases and prevent bugs before release.
• Integrate automated tests into CI/CD pipelines and maintain test environments.
• Verify REST API integrations and data states across services built with NestJS, PostgreSQL, and Prisma.
• Validate UI behavior in mobile and desktop views using modern frameworks like Next.js and TailwindCSS.

What We’re Looking For

• 3+ years of professional QA experience, ideally in a startup or fast-paced product environment.
• Strong understanding of STLC, SDLC, test case design, and bug lifecycle.
• Experience with automated testing tools such as Cypress, Playwright, Selenium, or similar.
• Familiarity with tools like Postman for API testing and scripting.
• Knowledge of browser-based testing for responsive web apps and component-driven UIs.
• Ability to write clear bug reports and test documentation that helps devs move fast.

Bonus Points

• Experience working with systems built on Next.js, NestJS, Prisma, or Firebase Auth.
• Exposure to LLMs and GenAI workflows (OpenAI, Vertex AI, LangChain, etc.)
• Past testing of admin panels, CRM tools, or multi-tenant SaaS dashboards.
• Understanding of security testing, data validation, and performance benchmarking.

What You'll Gain

• Direct ownership of QA for a fast-growing AI product line.
• Collaboration with engineering and product teams building real-world agentic systems.
• Deep exposure to testing AI and automation at the intersection of intelligence and usability.
• A portfolio of tested, reliable enterprise UIs used by real businesses every day.
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How to Apply

Please send:

• Your resume
• GitHub, test case samples, or automation scripts (if available)
• A short video (~3–5 min) explaining your QA approach to a complex system or release cycle

If you're excited about testing autonomous systems that operate in the real world—not just research labs—we’d love to hear from you.

Apply now and build what’s next in AI.

Note: We are only looking for candidates who can work in EST timezone. Preference will be given to Immediate Joiners.

JUTEQ is an AI-native and cloud-native technology consulting firm helping enterprises in financial services, telecom, and healthcare build intelligent, production-grade systems. We combine the power of GenAI, cloud architecture, and automation to deliver next-generation business tools.

We’re seeking a DevOps/Site Reliability Engineer (SRE) with experience in Google Cloud Platform (GCP) to lead and evolve our AI infrastructure as we scale multi-tenant agentic systems across automotive and enterprise use cases. This is a hands-on role working at the intersection of automation, observability, and production AI system reliability.

What You’ll Work On

Platform Reliability & Automation

• Own deployment pipelines, autoscaling, and high-availability for AI microservices running on GCP (Cloud Run, GKE, App Engine)
• Design and optimize CI/CD pipelines using Cloud Build, Skaffold, GitHub Actions
• Implement intelligent autoscaling strategies based on LLM cost, latency, and throughput
• Use Infrastructure as Code (Terraform, Deployment Manager) for repeatable cloud provisioning

Monitoring & Observability

• Deploy monitoring and alerting across Cloud Logging, Cloud Monitoring, and custom dashboards for agent performance metrics
• Define SLOs and SLIs for key services; implement failover and rollback strategies
• Build observability into agent workflows: latency, success rate, AI token consumption, prompt drift, etc.

Data & AI Infrastructure

• Manage access, scaling, and resilience of data services: BigQuery, Firestore, Memorystore, Cloud Storage, Pub/Sub
• Support model integration workflows with Vertex AI and third-party LLM providers (OpenAI, Anthropic, etc.)
• Monitor and secure retrieval pipelines (RAG, embedding generation, vector DBs)

Security & Compliance

• Implement and maintain IAM policies, workload identity, and service-to-service authentication
• Lead incident response and postmortem analysis for production outages
• Ensure systems comply with data residency, privacy, and SOC2/GDPR requirements

What We’re Looking For

Experience & Skills

• 4+ years of DevOps or SRE experience, with at least 2+ years on GCP
• Strong understanding of GCP products including Cloud Run, GKE, Cloud Build, BigQuery, Pub/Sub, Cloud Monitoring
• Experience with CI/CD and GitOps workflows (GitHub Actions, ArgoCD, etc.) and Observability/Monitoring
• Deep knowledge of containerization, Docker, and Kubernetes
• Familiarity with AI infrastructure (LLMs, prompt evaluation, LangChain/CrewAI patterns) is a strong plus
• Experience with alerting and logging using Prometheus, Grafana, or GCP-native tools
• Proficient in scripting (Python, Bash, Go preferred)

Bonus Points

• Experience managing infrastructure for AI agent systems or GenAI workloads
• Familiarity with multi-tenant SaaS platforms
• Understanding of RAG pipelines, embedding generation, or agent orchestration
• Certifications: Google Professional Cloud DevOps Engineer or equivalent

Why Join Us

• Shape the infrastructure behind real-world AI agents used by automotive dealerships and enterprises
• Work alongside AI developers, product engineers, and solution architects
• Ship fast in a zero-to-one environment while building for scale
• Own platform-level impact across reliability, security, cost, and developer productivity

How to Apply

Please send:

• Your resume highlighting DevOps/SRE experience on GCP
• GitHub or portfolio links showcasing infrastructure projects or CI/CD pipelines
• (Optional) A short Loom or video describing your favorite system you’ve built or scaled

JUTEQ is an AI-native and cloud-native technology consulting firm helping enterprises in financial services, telecom, and healthcare build intelligent, production-grade systems. We combine the power of GenAI, cloud architecture, and automation to deliver next-generation business tools.

We’re building an AI-powered platform that enables enterprises to automate complex workflows by letting AI agents navigate, reason, and operate within web applications autonomously.

We’re looking for a Browser Agent Developer to join our team and build the next generation of AI-driven browser automation technology.

What You’ll Do

• Build LLM-powered agents that can operate browsers intelligently (navigate, click, extract, fill forms, handle errors).
• Integrate reasoning and planning capabilities (e.g., task decomposition, multi-step workflows).
• Design APIs and orchestration layers to connect agents with enterprise data and systems.
• Collaborate with AI researchers and product teams to improve agent capabilities and UX.
• Optimize agent behavior for reliability, efficiency, and user experience.
• Debug and improve multi-tenant, production-grade browser agent systems.

What We’re Looking For

• 3+ years of software development experience.
• Strong programming skills in Python and TypeScript/JavaScript.
• Hands-on experience with LLMs (OpenAI, Anthropic, or similar).
• Experience with browser control frameworks (Playwright, Puppeteer).
• Solid understanding of prompt engineering, function calling, and agent architectures.
• Familiarity with APIs, microservices, and cloud platforms (AWS/GCP/Azure).

Bonus Points

• Experience with agent frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, etc.).
• Knowledge of reinforcement learning, planning algorithms, or tool-using agents.
• Experience deploying LLM-powered apps in production.
• Contributions to open-source AI/agent projects.

What You’ll Gain

• Work on cutting-edge LLM browser agents used by enterprises in real workflows.
• Opportunity to define and shape core agent behaviors from the ground up.
• Be part of a fast-growing team at the intersection of AI, automation, and enterprise systems.
• Build skills that will define the future of AI-first software.

Location: Remote (EST timezone overlap required)
Start: Immediate joiners preferred

Apply now and help us push the limits of what AI agents can do in the browser.