Python
JenkinsRequirements:-
- Must have good understanding of Python and Shell scripting with industry standard coding conventions
- Must possess good coding debugging skills
- Experience in Design & Development of test framework
- Experience in Automation testing
- Good to have experience in Jenkins framework tool
- Good to have exposure to Continuous Integration process
- Experience in Linux and Windows OS
- Desirable to have Build & Release Process knowledge
- Experience in Automating Manual test cases
- Experienced in automating OS / FW related tasks
- Understanding of BIOS / FW QA is a strong plus
- OpenCV experience is a plus
- Good to have platform exposure
- Must have good Communication skills
- Good Leadership capabilities & collaboration capabilities, as individual will have to work with multiple teams and single handedly maintain the automation framework and enable the Manual validation team
Shubham Vishwakarma
Full Stack Developer - Averlon
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PythonJob Summary
The Technical Lead will be responsible for overseeing and leading projects related to Azure Data Factory (ADF), Azure Databricks, SQL, Oracle PL/SQL, and Python. The role involves designing, developing, and implementing data solutions while ensuring they meet the business requirements and align with best practices. (1.) Key Responsibilities
1. Lead and manage end-to-end data engineering projects using azure data factory, azure databricks, sql, oracle pl/sql, and python.
2. Collaborate with stakeholders to gather and understand requirements for data pipelines and analytics solutions.
3. Design and develop etl processes, data models, and data integration solutions.
4. Provide technical guidance and mentorship to the team members.
5. Ensure data quality, data governance, and data security standards are maintained throughout the project lifecycle.
6. Troubleshoot and optimize data pipelines and processes for performance and efficiency.
7. Stay updated on the latest trends and technologies in data engineering and contribute to continuous improvement efforts.
Skill Requirements
1. Proficiency in azure data factory (adf) and azure databricks for building and managing data pipelines.
2. Strong experience with sql and oracle pl/sql for data querying and manipulation.
3. Advanced programming skills in python for scripting and data processing tasks.
4. Knowledge of data modeling, data warehousing concepts, and database design principles.
5. Ability to work in a collaborative team environment and communicate effectively with stakeholders.
6. Strong analytical and problem-solving skills with attention to detail.
7. Experience in data visualization tools and techniques is a plus.
Certifications: Relevant certifications in Azure Data Factory, Azure Databricks, SQL, Oracle PL/SQL, or Python are advantageous.
Skill (Primary)
Data Fabric-Azure-Azure Data Factory (ADF)
Python
Machine Learning (ML)Supercharge Your Career as a AI DevOps Engineer at Technoidentity!
At Technoidentity, we're a Data & AI product engineering company with over 15 years of expertise in building durable digital products, intelligent enterprise solutions, and scalable Data & AI platforms. As we continue expanding globally, it's the perfect time to join our team of tech innovators and make a lasting impact.
What’s in it for You?
We are looking for an AI DevOps Engineer with 0–3 years of experience who is passionate about AI, Cloud, DevOps, and Automation. The role involves building, deploying, and managing AI-powered applications, LLM solutions, and cloud-native platforms while ensuring reliability, scalability, security, and observability.
What Will You Be Doing?
- Develop and deploy AI/ML and Generative AI solutions using Python.
- Build applications leveraging LLMs, RAG, and AI agents.
- Create and maintain CI/CD pipelines for AI applications.
- Deploy and manage workloads using Docker and Kubernetes.
- Support cloud platforms (AWS, Azure, or GCP).
- Implement Infrastructure as Code (Terraform) and automation workflows.
- Monitor applications using observability tools such as Prometheus, Grafana, and logging platforms.
- Collaborate with engineering teams to ensure system reliability, performance, and security.
- Contribute to MLOps practices, AI accelerators, and reusable frameworks.
Requirements
What Makes You the Perfect Fit?
- Python programming (mandatory)
- Understanding of Machine Learning, LLMs, Prompt Engineering, and RAG
- Experience with OpenAI, LangChain, LlamaIndex, or Hugging Face
- Docker, Kubernetes, Git, and CI/CD tools
- AWS, Azure, or GCP
- PostgreSQL; MongoDB and Vector Databases are a plus
- Basic knowledge of MLOps, Terraform, and workflow orchestration tools (Airflow/Temporal)
- Familiarity with observability and monitoring tools
Qualifications
- Bachelor's degree in Computer Science, AI, Data Science, IT, or related field
- 0–3 years of experience in AI/ML, Software Engineering, Cloud, DevOps, or related areas
Nice to Have
- Experience with Agentic AI frameworks
- Knowledge of MLOps and AI platform operations
- Exposure to enterprise-grade monitoring, reliability engineering, and security best practices
Docker
KubernetesPrimary (Must Have):
5-7 years of total experience in IT industry
Necessary to have exposure to Azure Cloud
5-7 years of experience Build/Release and DevOps combined for Saas/Web/Desktop applications
5-7 years working with CI / CD like Jenkins or Bamboo or other tools
Experience in Kubernetes, Swarm and Docker
Experience in working with Linux (Centos/Ubuntu)
Experience with configuration and management tools (i.e. Terraform, Ansible, Salt)
Experience in architecting, maintaining, and streamlining our automated build and release pipeline from code compilation, automated testing, to deploying releases to multiple environments
You should be able to drive adoption of CI/CD, deployment automation, and release engineering standard methodologies
Detail-oriented and great problem solver
Comfortable giving feedback to team members and handling personal situations
Excellent at multi-tasking and able to handle competing priorities
Problem solving, digging into issues and owning tasks to completion
Strong team player who is open to give and receive feedback
A passion for technology and thrives in a dynamic environment with a focus on creative innovation over absolute completion
Communication and presentation skills
Key Responsibilities:
Responsible for the continuous and on-time delivery of application releases supporting mission-critical services
Support and improve our tools for continuous integration (CI) and continuous delivery (CD). You can demonstrate measurable improvements in our delivery pipelines
Responsible for navigating cloud solutions, on-premise solutions, and hybrid solutions
Responsible for infrastructure as code (IaC) tooling
Build automated release pipelines that package, test and deploy code
Build out and maintain a suitable tracking dashboards and metrics
PythonDockerKubernetesSkills Required:
- Good experience with programming language Python
- Strong experience in Docker.
- Good knowledge with any of the Cloud Platform like Azure.
- Must be comfortable working in a Linux environment.
- Must have exposure into IOT domain and its protocols ((Zigbee & BLE ,LoRa,Modbus)
- Must be a good team player.
- Strong Communication Skills
Amazon Web Services (AWS)
MongoDB-
Working with Ruby, Python, Perl, and Java
-
Troubleshooting and having working knowledge of various tools, open-source technologies, and cloud services.
-
Configuring and managing databases and cache layers such as MySQL, Mongo, Elasticsearch, Redis
-
Setting up all databases and for optimisations (sharding, replication, shell scripting etc)
-
Creating user, Domain handling, Service handling, Backup management, Port management, SSL services
-
Planning, testing & development of IT Infrastructure ( Server configuration and Database) and handling the technical issue related to server Docker and VM optimization
-
Demonstrate awareness of DB management, server related work, Elasticsearch.
-
Selecting and deploying appropriate CI/CD tools
-
Striving for continuous improvement and build continuous integration, continuous development, and constant deployment pipeline (CI/CD Pipeline)
-
Experience working on Linux based infrastructure
-
Awareness of critical concepts in DevOps and Agile principles
-
6-8 years of experience
KubernetesDockerJenkinsAs a MLOps Engineer in QuantumBlack you will:
Develop and deploy technology that enables data scientists and data engineers to build, productionize and deploy machine learning models following best practices. Work to set the standards for SWE and
DevOps practices within multi-disciplinary delivery teams
Choose and use the right cloud services, DevOps tooling and ML tooling for the team to be able to produce high-quality code that allows your team to release to production.
Build modern, scalable, and secure CI/CD pipelines to automate development and deployment
workflows used by data scientists (ML pipelines) and data engineers (Data pipelines)
Shape and support next generation technology that enables scaling ML products and platforms. Bring
expertise in cloud to enable ML use case development, including MLOps
Our Tech Stack-
We leverage AWS, Google Cloud, Azure, Databricks, Docker, Kubernetes, Argo, Airflow, Kedro, Python,
Terraform, GitHub actions, MLFlow, Node.JS, React, Typescript amongst others in our projects
Key Skills:
• Excellent hands-on expert knowledge of cloud platform infrastructure and administration
(Azure/AWS/GCP) with strong knowledge of cloud services integration, and cloud security
• Expertise setting up CI/CD processes, building and maintaining secure DevOps pipelines with at
least 2 major DevOps stacks (e.g., Azure DevOps, Gitlab, Argo)
• Experience with modern development methods and tooling: Containers (e.g., docker) and
container orchestration (K8s), CI/CD tools (e.g., Circle CI, Jenkins, GitHub actions, Azure
DevOps), version control (Git, GitHub, GitLab), orchestration/DAGs tools (e.g., Argo, Airflow,
Kubeflow)
• Hands-on coding skills Python 3 (e.g., API including automated testing frameworks and libraries
(e.g., pytest) and Infrastructure as Code (e.g., Terraform) and Kubernetes artifacts (e.g.,
deployments, operators, helm charts)
• Experience setting up at least one contemporary MLOps tooling (e.g., experiment tracking,
model governance, packaging, deployment, feature store)
• Practical knowledge delivering and maintaining production software such as APIs and cloud
infrastructure
• Knowledge of SQL (intermediate level or more preferred) and familiarity working with at least
one common RDBMS (MySQL, Postgres, SQL Server, Oracle)
KubernetesDockerOne of our US based client is looking for a Devops professional who can handle Technical as well as Trainings for them in US.
If you are hired, you will be sent to US for the working from there. Training & Technical work ratio will be 70% & 30% respectively.
Company Will sponsor for US Visa.
If you are an Experienced Devops professional and also given professional trainings then feel free to connect with us for more.
Implement integrations requested by customers
Deploy updates and fixes
Provide Level 2 technical support
Build tools to reduce occurrences of errors and improve customer experience
Develop software to integrate with internal back-end systems
Perform root cause analysis for production errors
Investigate and resolve technical issues
Develop scripts to automate visualization
Design procedures for system troubleshooting and maintenance
Multiple Clouds [AWS/Azure/GCP] hands on experience
Good Experience on Docker implementation at scale.
Kubernets implementation and orchestration.
DockerPythonResponsibilities
- Building and maintenance of resilient and scalable production infrastructure
- Improvement of monitoring systems
- Creation and support of development automation processes (CI / CD)
- Participation in infrastructure development
- Detection of problems in architecture and proposing of solutions for solving them
- Creation of tasks for system improvements for system scalability, performance and monitoring
- Analysis of product requirements in the aspect of devops
- Managing a team of DevOps, control of task deliveries
- Incident analysis and fixing
Technology stack
Linux, Bash, Salt/Ansible, LXC, libvirt, IPsec, VXLAN, Open vSwitch, OpenVPN, OSPF, BIRD, Cisco NX-OS, Multicast, PIM, LVM, software RAID, LUKS, PostgreSQL, nginx, haproxy, Prometheus, Grafana, Zabbix, GitLab, Capistrano
Skills and Experience
- Understanding of the distributed systems principles
- Understanding of principles for building a resistant network infrastructure
- Experience of Ubuntu Linux administration (Debian-like will be a plus)
- Strong knowledge of Bash
- Experience of working with LXC-containers
- Understanding and experience with infrastructure as a code approach
- Experience of development idempotent Ansible roles
- Experience with relational databases (PostgeSQL), ability to create simple SQL queries
- Experience with git
- Experience with monitoring and metric collect systems (Prometheus, Grafana, Zabbix)
- Understanding of dynamic routing (OSPF)
Preferred experience
- Experience of working with highload zero-downtown environments
- Experience of coding on Python
- Experience of working with IPsec, VXLAN, Open vSwitch
- Knowledge and experience of working with network equipment Cisco
- Experience of working with Cisco NX-OS
- Knowledge of principles of multicast protocols IGMP, PIM
- Experience of setting multicast on Cisco equipment
- Experience of working with Solarflare Onload
- Experience administering Atlassian products
Python
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon