Ambience Services

Frontend Engineer

• - Develop and maintain responsive, high‑quality user interfaces using modern front‑end frameworks
• - Write clean, maintainable, and efficient code with a strong focus on usability and performance
• - Collaborate with designers to translate UI/UX wireframes into functional components
• - Work closely with backend engineers to integrate APIs and ensure smooth end‑to‑end functionality
• - Participate in technical discussions and contribute ideas to improve the front‑end architecture
• - Support the team in delivering on goals and enhancing existing features and components

Front-End Developer

Machine Learning Engineer

• Design, build, and optimize AI‑driven agents and autonomous workflows
• Develop, fine‑tune, and evaluate machine learning models for production use
• Architect and implement data pipelines, model‑serving infrastructure, and agent orchestration components
• Lead experimentation, research, and prototyping of new AI techniques and agent frameworks
• Collaborate with cross‑functional teams to integrate AI capabilities into applications and platforms
• Ensure performance, reliability, and scalability of deployed models and agent systems
• Contribute to technical strategy and mentor other engineers in AI/ML best practices

AI/ML Engineer – Agent Specialist

Cloud Engineer

• Set up and evolve cloud-based environments for SaaS products (multi-environment setups, security, scalability, cost awareness)
• Design and implement CI/CD pipelines for applications and infrastructure (build/test/release automation, branching strategies, release confidence)
• Infrastructure as Code (IaC): create reusable modules, version-controlled environments, and automated provisioning (e.g., Terraform/CloudFormation/Bicep)
• Support the transition from Azure to AWS by delivering hands-on implementations on AWS, while maintaining and improving existing Azure workloads (migration waves, risk management, service continuity)
• Implement and operate multi-cloud foundations and shared services (landing zones, identity & access, networking, secrets, tagging/FinOps) together with the team
• Support Data Engineering workloads by provisioning and operating data platforms and pipelines (batch/streaming), ensuring reliability and performance
• Implement and operate observability for services and pipelines using Prometheus and Grafana (dashboards, alerting, SLO-oriented monitoring)
• Collaborate with engineers to improve deployment patterns (containers/Kubernetes when applicable), troubleshooting and incident response
• Introduce DevOps practices (automation, documentation, runbooks) and share knowledge with the team to improve day-to-day delivery
• Work with the security officer to apply security best practices (least privilege, secrets management, vulnerability scanning) and support compliance requirements