We are hiring!

We are looking for skilled professionals to drive innovation, growth, and business success.

DevOps Engineer

We are seeking an experienced DevOps Engineer to design, implement, and maintain cloud infrastructure and CI/CD pipelines. You will work closely with development, operations, and security teams to automate deployments, improve system reliability, and enhance scalability. Your expertise in cloud platforms, containerization, and infrastructure-as-code will be critical in ensuring smooth and efficient software delivery.

Implement and maintain infrastructure-as-code using tools like Terraform and CloudFormation.
Work with containerization and orchestration tools like Docker and Kubernetes.
Ensure security best practices in cloud infrastructure and DevOps workflows.
Monitor system performance, troubleshoot issues, and implement proactive improvements.
Automate repetitive tasks to improve operational efficiency and reduce downtime.
Collaborate with development teams to improve software release processes.
Optimize cloud infrastructure for high availability, performance, and cost-efficiency.
Design, implement, and manage CI/CD pipelines for automated software deployment.

Required Skills
3+ years of experience in code development for automation in service delivery and operations
Bachelor’s or Master’s degree in Computer Science, IT, or a related field.
Proven experience in DevOps, cloud computing, or site reliability engineering.
Strong knowledge of cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
Experience with CI/CD tools like Jenkins, GitLab CI/CD, or GitHub Actions.
Proficiency in scripting languages such as Python, Bash, or PowerShell.
Hands-on experience with monitoring and logging tools (Prometheus, Grafana, ELK Stack).
Understanding of networking, security best practices, and system architecture.
Excellent problem-solving and troubleshooting skills.
Certification in cloud platforms in AWS is preferred.

Design end-to-end AI solutions, integrating machine learning models with cloud platforms and enterprise applications.
Collaborate with data scientists and AI engineers to define AI system architecture and deployment strategies.
Evaluate business requirements and translate them into scalable AI-driven solutions.
Optimize AI workloads for cloud environments, ensuring performance, security, and cost efficiency.
Implement MLOps best practices to streamline AI model development, deployment, and monitoring.
Guide DevOps and engineering teams in implementing AI infrastructure using cloud-native technologies.
Provide technical leadership in AI solution design, ensuring alignment with industry best practices.
Stay up to date with emerging AI technologies and trends to drive innovation in AI solutions.

5+ years of experience in AI architecture, machine learning engineering, or cloud-based AI solutions.
Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field.
Proven experience as an AI Solution Architect, AI Engineer, or similar role.
Expertise in cloud platforms (AWS, Azure, GCP) and AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn).
Strong understanding of AI model lifecycle management and MLOps tools (MLflow, Kubeflow, TensorFlow Serving).
Experience with data engineering, big data technologies (Apache Spark, Kafka), and database systems.
Proficiency in programming languages such as Python, Java, or Go.
Hands-on experience with containerization (Docker, Kubernetes) and serverless computing.
Excellent problem-solving and analytical skills, with the ability to design scalable AI architectures.

Collect, clean, and preprocess data for machine learning models and business insights.
Develop, test, and optimize predictive models using statistical and AI techniques.
Implement machine learning algorithms in cloud-based and on-premise environments.
Collaborate with AI engineers and data engineers to integrate models into production.
Utilize big data technologies to analyze large datasets and extract actionable insights.
Design and develop data visualizations and dashboards for stakeholders.
Conduct A/B testing and statistical analysis to support business decision-making.
Stay up to date with the latest trends in AI, ML, and data science.
Required Skills
3+ years of experience in data science, machine learning, or statistical analysis.
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
Strong proficiency in Python or R, with experience in ML libraries (TensorFlow, PyTorch, Scikit-learn).
Expertise in data visualization tools such as Tableau, Power BI, or Matplotlib.
Experience with SQL and NoSQL databases for data querying and manipulation.
Knowledge of cloud platforms (AWS, Azure, GCP) and big data frameworks (Apache Spark, Hadoop).
Understanding of data engineering concepts, including ETL pipelines and data warehousing.
Strong problem-solving and analytical skills, with the ability to work in a team-oriented environment.
Certifications in data science, AI, or cloud platforms (AWS Certified Machine Learning, Google Data Engineer, etc.).