Commit Offshore

Key Responsibilities:

• Java Development: Design and develop backend services using Java and the Spring Framework (Spring Boot, Spring Cloud).
• Microservices: Architect and implement scalable microservices for high availability and performance.
• Helm & Kubernetes: Use Helm and Kubernetes for container orchestration and automated deployment.
• Production Support: Participate in the "Blender" on-call rotation (approximately once a month) to resolve production issues.
• Collaboration: Work closely with cross-functional teams to define, design, and optimize technical solutions.

Skills & Qualifications:

• Java & Spring: 5+ years of hands-on experience with Java and Spring (Spring Boot, Spring Cloud).
• Microservices: Experience building and deploying microservices in a distributed environment.
• Helm/Kubernetes: Familiarity with Helm and Kubernetes for deploying and managing applications in the cloud.
• Cloud Platforms: Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
• On-Call Support: Willingness to participate in the Blender on-call rotation and resolve production incidents.

Soft Skills:

• Strong problem-solving and troubleshooting skills.
• Excellent team player with effective communication and collaboration skills.
• Adaptable in a fast-paced, dynamic environment.

Key Responsibilities:

• Java Development: Design and develop backend services using Java and the Spring Framework (Spring Boot, Spring Cloud).
• Microservices: Architect and implement scalable microservices for high availability and performance.
• Helm & Kubernetes: Use Helm and Kubernetes for container orchestration and automated deployment.
• Production Support: Participate in the "Blender" on-call rotation (approximately once a month) to resolve production issues.
• Collaboration: Work closely with cross-functional teams to define, design, and optimize technical solutions.

Skills & Qualifications:

• Java & Spring: 5+ years of hands-on experience with Java and Spring (Spring Boot, Spring Cloud).
• Microservices: Experience building and deploying microservices in a distributed environment.
• Helm/Kubernetes: Familiarity with Helm and Kubernetes for deploying and managing applications in the cloud.
• Cloud Platforms: Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
• On-Call Support: Willingness to participate in the Blender on-call rotation and resolve production incidents.

 We are looking for a talented Cloud Infrastructure Engineer to join our dynamic team and help enhance our cloud infrastructure to better serve our clients.

Key Responsibilities:

• Design, deploy, and manage scalable cloud infrastructure across AWS, Azure, GCP, Alicloud, and Oracle Cloud, as well as on-premise solutions.
• Implement configuration management using tools like Ansible and Puppet to maintain system consistency and reliability.
• Utilize Infrastructure as Code (IaC) methodologies with Terraform and CloudFormation to automate and streamline cloud resource provisioning.
• Manage containerized applications using Docker, Podman, and Kubernetes to ensure high availability and performance.
• Administer and optimize Linux and FreeBSD operating systems for efficiency and security.
• Configure and maintain web servers (Nginx, Apache) and application servers (Tomcat, Jetty, uWSGI) to support our solutions.
• Design and implement networking solutions, including routing, switching, SDN, VPN, VPC, LAN, and WAN.
• Manage and optimize SQL (PgSQL, MySQL) and NoSQL databases (MongoDB, Cassandra, Elasticsearch, Redis) to support data-driven applications.
• Oversee virtualization environments using KVM, OpenVZ, VMWare ESXI, and Hyper-V for resource management.
• Set up comprehensive monitoring and alerting solutions with Zabbix, Cacti, Nagios, Datadog, CloudWatch, ELK, and NewRelic to ensure system health.
• Integrate and manage message brokers such as Kafka, RabbitMQ, and ActiveMQ for effective data processing.
• Utilize discovery tools like Consul and Zookeeper to maintain service health and availability.
• Develop and maintain scripts in Bash and Python for automation and system management tasks.
• Collaborate with development teams using CI tools like Jenkins and GitLab pipelines to enhance deployment workflows.

Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• Proven 5+ years of experience with cloud platforms (AWS, Azure, GCP, Alicloud, Oracle Cloud) and on-premise infrastructure.
• Experience with Datadog, Github Actions, CI/CD, Docker, Octopus
• AWS Services: Lambda, Lambda@Edge, ECS, RDS, Aurora, Postgres, Dynamo, Redis, Cloudfront, Cloudformation, SQS, SNS, Cloudwatch
• Strong knowledge of configuration management tools (Ansible, Puppet) and IaC tools (Terraform, CloudFormation).
• Experience with container orchestration and management (Docker, Kubernetes).
• Proficient in Linux and FreeBSD operating systems.
• Familiarity with web and application server technologies (Nginx, Apache, Tomcat, Jetty, uWSGI).
• Understanding of networking concepts and protocols, including SDN, VPN, VPC, LAN, and WAN.
• Experience with SQL and NoSQL databases.
• Hands-on experience with virtualization technologies (KVM, OpenVZ, VMWare ESXI, Hyper-V).
• Knowledge of monitoring and logging tools (Zabbix, Nagios, Datadog, ELK).
• Experience with message brokers and service discovery tools.
• Proficient in scripting languages such as Bash and Python.
• Familiarity with CI/CD processes and tools (Jenkins, GitLab).

Preferred Qualifications:

• Cloud certifications (e.g., AWS Certified Solutions Architect, Azure Solutions Architect Expert, Google Cloud Professional).
• Familiarity with Agile methodologies and DevOps practices.

DevOps Engineer     

We are looking for a talented DevOps Engineer to join our team, working on cutting-edge AI infrastructure that powers our developer tools. If you have a passion for cloud infrastructure, love automating everything, and are eager to help shape the future of AI-powered development platforms, this is the perfect opportunity for you.   

Why Join Us?   

• Be part of an innovative team at the forefront of AI infrastructure for software developers. 

• Work with cutting-edge cloud technologies and modern DevOps practices. 

• Own and shape the infrastructure that powers AI agents and development tools. 

• Collaborate with top-tier engineers building the next generation of developer tools. 

• Solve complex challenges in a fast-paced, growing company. 

• Enjoy a fun work environment with exciting opportunities as we rapidly expand.  

 Our tech stack 

  Pulumi (TypeScript) (Huge advantage) , GitHub Actions (Big advantage) , AWS (ECS, RDS, VPC, Lambda, S3, ECR), Docker, , Datadog, PostgreSQL, Python, Node.js.   

Responsibilities:   You'll play a key role in maintaining, optimizing, and scaling our cloud infrastructure. Responsibilities include managing infrastructure as code with Pulumi, maintaining comprehensive CI/CD pipelines with GitHub Actions, orchestrating containerized services on ECS, and ensuring reliable deployments across dev and production environments. You'll work with microservices architecture, optimize build and deployment processes, configure monitoring and alerting, and implement security best practices.  

 Preferred Qualifications:   

• 3 to 5 years of DevOps/Infrastructure Engineering experience 

• Strong AWS expertise with hands-on experience in ECS/Fargate, VPC networking, RDS, IAM, and CloudWatch 

• Experience with Infrastructure as Code tools such as Pulumi must know or Terraform, or CloudFormation 

• Extensive experience with CI/CD pipelines (GitHub Actions preferred) • Deep knowledge of Docker and containerization best practices 

• Proficiency in TypeScript/JavaScript, Python, and Bash 

• Strong Linux/Unix system administration and command-line skills 

• Understanding of networking (TCP/IP, DNS, load balancing, network security) 

• Advantage - Experience with Pulumi (TypeScript) 

• Advantage - Experience with Datadog or similar APM tools 

• Advantage - PostgreSQL administration and optimization experience • Advantage - Experience with gRPC and microservices architectures 

• Advantage - Multi-account AWS setup experience 

• Advantage - Experience with load testing tools (Locust, k6, etc.) 

• Advantage - Experience with monorepo CI/CD strategies  

We are looking for a DevOps Ninja! If you have a strong passion for building next-generation MLOps platforms, you should strongly consider joining us as a Senior DevOps engineer. You will lead large-scale, cross-team efforts and work closely with R&D architects to provide the best DevOps angles for SaaS solutions and also be customer facing providing our customers with the best cloud solutions.

Senior DevOps Engineer – Job Description

As a Senior DevOps Engineer, you will…

• Lead the team towards technical solutions guided by a strong understanding of the latest and greatest technologies such as Kubernetes, Helm, Terraform, and more
• Design, implement, and manage cloud and containerized architectures in AWS and Azure, GCP, OpenStack
• Work with a large scale of customers with extensive use of Kubernetes and Helm
• Tackle large-scale production issues and bring out-of-the-box thinking to the table
• Evaluate new cloud-native technologies and vendor products to continuously improve our SaaS offerings

To be a Senior DevOps Engineer, you need…

• 5+ years of relevant DevOps experience in large-scale production environments
• 2+ years of infrastructure automation, configuration management, or container orchestration
• 2+ years of experience in Python or another advanced programming language
• Strong ability to lead, design, and execute cross-organization projects
• High experience managing container and infrastructure orchestration tools (e.g., Kubernetes, Helm, Terraform)
• Hands-on experience administering public clouds (AWS or Azure, GCP)
• Experience building CI/CD pipelines for applications and microservices

We are seeking a highly skilled and customer-oriented Senior DevOps Engineer to design, implement, and maintain complex AWS environments. The ideal candidate will have a proven track record of delivering reliable, scalable, and secure solutions. 

Role Responsibilities: 

• Design and implement complex AWS environments, including infrastructure as code (IaC) and container orchestration (Kubernetes). • Build and maintain robust application infrastructure. 

• Advise on data protection and security best practices in the cloud. 

• Assist with hybrid environments requiring integration with on-premises networks. 

• Deliver complex production environments based on Kubernetes, IaC, CI/CD, and sensitive data sources. 

Required Skills and Experience: 

• 5+ years of hands-on experience with AWS Cloud services 

• Deep understanding and extensive deployment experience with EC2, S3, RDS, VPC, VPN, Network Segmentation, Security Groups, ELB, and ASG 

• Proven expertise with EKS or ECS for container orchestration 

• Proficiency in automation provisioning using Terraform or CloudFormation 

• Strong proficiency in Windows and Linux operating systems 

• In-depth knowledge of IAM and Roles 

• Solid understanding of SSH, HTTPS, certificates, and encryption protocols 

• Experience with deployment tools like Azure DevOps, AWS CodePipeline, or GitHub Actions 

• Proven ability to design and deploy highly available, redundant, and disaster recovery solutions 

• Excellent written and verbal communication skills, including technical documentation 

• Strong teamwork, problem-solving, and self-motivation skills 

• Previous experience with security standards and regulations (preferred) 

Desired Skills: 

• Experience with security tools like vulnerability scanners, intrusion detection systems, and SIEM 

• Knowledge of security principles, such as least privilege, role-based access control, and

About the Role We are looking for a Senior MLOps Architect to lead high-stakes AI and Data projects for our enterprise customers. In this role, you will act as the technical authority, helping clients bridge the gap between experimental data science and production-grade operations primarily on Google Cloud Platform. You will lead projects that involve building end-to-end MLOps pipelines from scratch, migrating workloads to Vertex AI, and standardizing model deployment. You will usually act as the "trusted advisor" owning the architecture and the delivery. 

Key Responsibilities 

● Customer Leadership: Lead technical kickoffs, discovery workshops, and architecture reviews directly with client CTOs, VP R&D, and Data Science leads. 

● Architecture & Design: Design robust, scalable MLOps architectures using Google Cloud Platform services (Vertex AI, GKE, BigQuery, Cloud Build, Cloud Storage). 

● Implementation & Automation: Build "Golden Paths" for model deployment. Implement CI/CD pipelines for ML, automated retraining workflows, and model monitoring systems to allow Data Scientists to deploy self-sufficiently. 

● Production Engineering: Operationalize ML models in high-scale environments. Troubleshoot complex infrastructure issues (e.g., GPU provisioning, container orchestration, scaling strategies). 

● Strategic Advisory: Advise customers on best practices for MLOps maturity, cost optimization (FinOps for AI), and data governance. Requirements (Must Have) 

● MLOps Experience: At least 3+ years specialized in MLOps and building production ML pipelines. 

● Google Cloud Expert: Deep, hands-on experience with GCP core services (Compute Engine, GKE, IAM, Networking) and specifically Vertex AI (Pipelines, Feature Store, Model Registry).

● Customer-Facing Skills: Proven ability to lead projects, manage stakeholders, and explain complex technical concepts to clients. 

● Containerization & Orchestration: Strong proficiency with Docker and Kubernetes (GKE). 

● Coding: Strong proficiency in Python and SQL. 

● CI/CD for ML: Experience implementing pipelines using tools like Cloud Build, GitHub Actions, or Jenkins. Big Advantage (Nice to Have) ● Databricks Expertise: Experience with the Databricks Lakehouse platform, Unity Catalog, and MLflow is a major plus. Many of our clients use Databricks alongside GCP, so this skill will be highly valued. 

● Certifications: Google Cloud Professional Machine Learning Engineer or Professional Cloud Architect. 

● GenAI Experience: Experience deploying Large Language Models (LLMs) or working with Gemini/Claude APIs in production.

Key Responsibilities:

• Backend Development: Develop, optimize, and maintain robust backend applications using Python (Django is a plus).
• Microservices Architecture: Design and implement scalable, efficient microservices architectures to support business needs.
• Cloud Solutions: Leverage AWS services (e.g., ECS, EKS, Lambda, S3, RDS) to design, develop, and deploy cloud-based applications.
• Kubernetes Management: Work with Kubernetes (K8s) to deploy and manage containerized applications ensuring smooth and efficient operations.
• Performance & Reliability: Ensure backend systems maintain optimal performance, reliability, and security to meet business and customer requirements.
• Collaboration & Strategy: Work closely with cross-functional teams to define system architecture and drive technical strategies for product development.
• Troubleshooting & Optimization: Identify and troubleshoot complex issues, applying solutions to improve system efficiency and reduce downtime.

Requirements:

• Experience: 7+ years of professional experience in software development, with a strong focus on backend technologies.
• Technical Skills:
  • Proficiency in Python (Django experience is a bonus).
  • In-depth understanding of Kubernetes (K8s) for container orchestration and management.
  • Experience in developing and deploying cloud solutions using AWS services, including ECS, EKS, Lambda, S3, and RDS.
  • Strong background in microservices architecture and distributed systems.
• Database Knowledge: Experience working with both relational and NoSQL databases.
• Problem-Solving: Strong debugging skills and a deep understanding of performance optimization techniques.
• Team Player: Ability to collaborate effectively with other developers, product managers, and engineers to ensure the success of key projects.

Preferred Qualifications:

• Knowledge of continuous integration and continuous delivery (CI/CD) pipelines.
• Experience with containerization tools like Docker.
• Familiarity with DevOps principles and practices

We’re building the next generation of AI-powered developer tools—systems that understand large codebases, automate real engineering work, and integrate directly into how developers build software.

We’re a fast-growing, fully remote, international company operating at the edge of AI, infrastructure, and developer productivity. This role is for engineers who enjoy hard problems, high ownership, and building things that didn’t exist before.

As a Senior Full-Stack Engineer, you’ll take ownership of critical parts of the platform—from backend architecture to frontend experiences used daily by developers. This is not a feature-factory role.

You’ll often work independently on complex initiatives, making architectural decisions, untangling difficult technical problems, and shipping solutions that scale. You’ll collaborate closely with AI engineers, but you’ll be expected to drive execution and technical direction.

What You’ll Build:

• Scalable backend services and APIs that power AI-driven automation
• High-quality frontend experiences using React and TypeScript, focused on performance and usability
• Systems that analyze and operate on large, real-world codebases
• Integrations that embed AI assistants directly into developer workflows
• Infrastructure and systems optimized for speed, reliability, and iteration

Tech Stack:

• Frontend: React.js, TypeScript
• Backend: Node.js or Python
• Infrastructure: AWS (managed services), Postgres, Redis

What We’re looking for:

• 5+ years of full-stack engineering experience in production environments
• Designing and owning complex systems end-to-end
• Making pragmatic architectural decisions in fast-moving environments
• Working with minimal process and high trust
• Solving hard problems without needing step-by-step direction
• Experience in early-stage or fast-scaling startups
• Technical leadership or ownership over major initiatives
• Familiarity with AI-powered tools, CI/CD, or Infrastructure as Code