DevSecops- Information Security Architect

Job Title : Senior Python Backend Developer

Experience Required : 5+ Years

Location : Gurgaon

Joining : Immediate Joiner Preferred

Employment Type : Full-Time

Job Summary :

We are looking for a highly skilled Senior Python Backend Developer with a minimum of 5 years of experience in Python and its modern web frameworks.

The ideal candidate will be responsible for developing scalable backend services, designing robust APIs, and ensuring optimal performance and security of backend systems.

Mandatory Skills : Python, Django, Flask, Streamlit, Starlette, REST API development, scalable backend services.

Key Responsibilities :

• Design, build, and maintain RESTful APIs and backend systems using Python.
• Work with frameworks such as Django, Flask, Streamlit, Starlette.
• Develop scalable and high-performance backend services.
• Collaborate with frontend developers and product teams to deliver seamless integrations.
• Write clean, maintainable, and testable code.
• Troubleshoot and resolve performance and scalability issues.
• Ensure code quality through automated testing and code reviews.

Required Skills :

• Minimum 5 years of backend development experience in Python.
• Strong expertise in Django, Flask, Streamlit, and/or Starlette.
• Proven experience with API design and development.
• Strong understanding of system architecture, data modeling, and scalability best practices.
• Familiarity with CI/CD pipelines, Docker, and cloud environments is a plus.

Nice to Have :

• Experience with async programming (e.g., using FastAPI, Starlette).
• Familiarity with PostgreSQL, MongoDB, or other relational/noSQL databases.
• Exposure to microservices architecture.

We are seeking a talented and experienced ServiceNow Developer to join our dynamic team. The ideal candidate will have a strong background in developing and customizing ServiceNow applications, with a deep understanding of the platform's modules and capabilities. This role offers an exciting opportunity to work on diverse projects and collaborate with leading industry professionals.

Key Responsibilities:

• Develop and customize ServiceNow applications and modules based on business requirements.
• Create and manage ServiceNow business rules, script includes, UI actions, and other scripting elements.
• Design and implement ServiceNow integrations using REST and SOAP web services.
• Configure and customize ServiceNow forms, lists, reports, and dashboards.
• Utilize ServiceNow Flow Designer and Orchestration to automate workflows.
• Collaborate with cross-functional teams to gather requirements and deliver effective solutions.
• Troubleshoot and resolve technical issues related to ServiceNow.
• Maintain system documentation and user guides.

Requirements:

• Proficiency in ServiceNow modules, including ITSM, ITOM, ITBM, and ITAM.
• Strong knowledge of JavaScript for client-side and server-side scripting.
• Experience with ServiceNow Studio, Flow Designer, and IntegrationHub.
• Familiarity with REST and SOAP web services for system integrations.
• Understanding of relational databases and SQL.
• ServiceNow Certified System Administrator and/or ServiceNow Certified Application Developer (preferred).
• Previous experience in a ServiceNow Developer role with a track record of successful projects.
• Strong problem-solving skills and the ability to communicate technical concepts to non-technical stakeholders.
• Experience with Agile methodologies and project management principles.

Preferred Qualifications:

• Experience with other ITSM tools and platforms.
• Additional ServiceNow certifications (e.g., Certified Implementation Specialist) are a plus.
• A degree in Computer Science, Information Technology, or a related field.

Job Description

We are looking for an experienced engineer to join our data science team, who will help us design, develop, and deploy machine learning models in production. You will develop robust models, prepare their deployment into production in a controlled manner, while providing appropriate means to monitor their performance and stability after deployment.

What You’ll Do will include (But not limited to):

• Preparing datasets needed to train and validate our machine learning models
• Anticipate and build solutions for problems that interrupt availability, performance, and stability in our systems, services, and products at scale.
• Defining and implementing metrics to evaluate the performance of the models, both for computing performance (such as CPU & memory usage) and for ML performance (such as precision, recall, and F1)
• Supporting the deployment of machine learning models on our infrastructure, including containerization, instrumentation, and versioning
• Supporting the whole lifecycle of our machine learning models, including gathering data for retraining, A/B testing, and redeployments
• Developing, testing, and evaluating tools for machine learning models deployment, monitoring, retraining.
• Working closely within a distributed team to analyze and apply innovative solutions over billions of documents
• Supporting solutions ranging from rule-bases, classical ML techniques  to the latest deep learning systems.
• Partnering with cross-functional team members to bring large scale data engineering solutions to production
• Communicating your approach and results to a wider audience through presentations

Your Qualifications:

• Demonstrated success with machine learning in a SaaS or Cloud environment, with hands–on knowledge of model creation and deployments in production at scale
• Good knowledge of traditional machine learning methods and neural networks
• Experience with practical machine learning modeling, especially on time-series forecasting, analysis, and causal inference.
• Experience with data mining algorithms and statistical modeling techniques for anomaly detection in time series such as clustering, classification, ARIMA, and decision trees is preferred.
• Ability to implement data import, cleansing and transformation functions at scale
• Fluency in Docker, Kubernetes
• Working knowledge of relational and dimensional data models with appropriate visualization techniques such as PCA.
• Solid English skills to effectively communicate with other team members

Due to the nature of the role, it would be nice if you have also:

• Experience with large datasets and distributed computing, especially with the Google Cloud Platform
• Fluency in at least one deep learning framework: PyTorch, TensorFlow / Keras
• Experience with No–SQL and Graph databases
• Experience working in a Colab, Jupyter, or Python notebook environment
• Some experience with monitoring, analysis, and alerting tools like New Relic, Prometheus, and the ELK stack
• Knowledge of Java, Scala or Go-Lang programming languages
• Familiarity with KubeFlow
• Experience with transformers, for example the Hugging Face libraries
• Experience with OpenCV

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

#LI-Remote

Role Responsibilities

• Support Infor WMS 2000
• Work on enhancement/customization on Infor WMS 2000
• Analysis of business requirements
• Application maintenance and enhancement
• Testing and documenting
• Supporting current software package

• Azure Devops - Working experience in Azure yaml pipelines. (Note – Some say they worked in yaml but it’s for Jenkins and not Azure devops)
• Azure – Infrastructure automation using Terraform/ARM templates. (Note – Some say that they worked in terraform but it’s for AWS and not Azure). Please confirm Terraform for Azure infrastructure automation.
• Powershell scripting to automate and deploy .Net applications.