NodeJS Developer

About the Role

We are looking for passionate and driven interns across multiple technology domains including Frontend Development, Backend Development, DevOps, AI/ML, and Data Engineering. This internship offers hands-on experience in real-world projects, collaboration with cross-functional teams, and exposure to modern tools and technologies. 

Domains & Responsibilities 

Frontend Development 

• Build responsive and user-friendly web interfaces  
• Translate UI/UX designs into functional applications  
• Optimize performance and ensure cross-browser compatibility  

 Backend Development 

• Develop APIs and server-side logic  
• Work with databases and data storage solutions  
• Ensure application security and performance  

 DevOps 

• Assist in CI/CD pipeline setup and automation  
• Manage deployments and cloud infrastructure  
• Monitor system performance and reliability  

 AI / Machine Learning 

• Develop and train ML models  
• Work on NLP, automation, or AI-driven features  
• Analyze datasets and evaluate model performance  

 Data Engineering 

• Build and maintain data pipelines (ETL/ELT)  
• Ensure data quality and availability  
• Work with large datasets and optimize data workflows  

 Required Skills (Any Domain) 

• Frontend: HTML, CSS, JavaScript, React/Vue/Angular  
• Backend: Node.js / Python / Java / PHP, APIs, databases  
• DevOps: Linux, Git, CI/CD basics, cloud fundamentals  
• AI/ML: Python, ML basics, TensorFlow/PyTorch/Scikit-learn  
• Data Engineering: SQL, Python, data processing concepts  

 Good to Have 

• Knowledge of Git and version control  
• Basic understanding of cloud platforms (AWS/Azure/GCP)  
• Problem-solving mindset and willingness to learn  
• Exposure to real-world or academic projects  

 Who Should Apply 

• Students or recent graduates in Computer Science, IT, or related fields  
• Candidates with strong interest in any of the above domains  
• Self-learners with project experience are highly encouraged  

 Internship Details 

• Duration: 3–6 months  
• Mode: Remote  
• Certificate + PPO (Pre-Placement Offer) based on performance  

 What You’ll Gain 

• Hands-on experience with real projects  
• Mentorship from experienced professionals  
• Exposure to industry tools and workflows  
• Opportunity to convert to a full-time role 

Senior DevOps Engineer

AWS Infrastructure, Kubernetes & Production Operations

📍 Mumbai (On-site) | Full-time | 5-8 years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Senior DevOps Engineer for a dedicated client engagement building an AI platform that turns a written prompt into a working, deployed web application.

The platform runs entirely on our own Kubernetes on AWS in Mumbai: multiple clusters, self-hosted Kafka, PostgreSQL, Redis and a complete observability stack, with untrusted AI-generated code executing inside isolated sandboxes.

This role owns that infrastructure end to end.

The mandatory requirement is hands-on production ownership of self-managed Kubernetes and self-hosted stateful services.

This is not a managed-services role: almost nothing here is a click in a console, and there is no platform team above you to escalate to.

You will pair daily with the Tech Architect who owns the architecture, and you own its execution, which covers clusters, networking, pipelines, observability, isolation, and the monthly cloud bill as a number you can explain line by line.

The role carries a deliberate path into LLM infrastructure over the first year, and we are saying so up front because we want someone who wants that direction.

A typical week includes rehearsing a cluster upgrade in a lower environment, tracing an unexplained cost line to its source, tuning autoscaling so non-production shuts down cleanly overnight, and hardening the boundary that keeps AI-generated code away from everything else.

Responsibilities:

Kubernetes Platform Ownership

Own multiple EKS clusters separated by trust boundary, covering platform services, messaging, sandboxed build environments, and hosting for customers' published applications.

Node pools, taints and tolerations, resource requests versus limits, pod disruption budgets, and the scheduling decisions that determine whether a cluster is efficient or merely large.

Plan and execute version upgrades without customer-visible downtime.

Infrastructure as Code

Everything in Terraform, with no console changes that are not in code.

Build reusable cluster modules rather than copies.

Keep state and reality in sync, and treat drift as a defect.

CI/CD and Release Engineering

Own the GitHub Actions pipelines and self-hosted runners: OIDC-based AWS authentication with no stored credentials, image builds, and rollouts across development, QA and UAT.

Move manifest templating from scripted substitution to Kustomize or Helm.

Make a rollback as routine as a deploy.

Network Architecture and Workload Isolation

VPC and subnet design, ingress through load balancers and service mesh, and eBPF-based network policy.

The platform runs code we did not write, so the isolation boundary is a primary deliverable: default-deny egress, kernel-level sandboxing for untrusted workloads, no platform credentials inside tenant pods, and one project per pod with nothing shared between customers.

Observability

Operate a self-hosted stack of Prometheus, Grafana, Loki, Tempo, OpenTelemetry and Alertmanager.

Build alerts engineers trust rather than mute.

Know what belongs in a metric, a log and a trace, and keep metric cardinality under control as tenant count grows.

Autoscaling and Capacity

Node autoscaling with Karpenter, and workload autoscaling on the signal that actually matters, which is queue depth or a schedule rather than CPU wherever CPU misleads.

Implement scale-to-zero across non-production and warm-pool patterns where cold starts are unacceptable.

Size capacity from measurement, not assumption.

Cost Operations

Own the cloud bill as an engineering artifact.

Attribute spend per cluster and per environment, right-size against real utilisation, apply Spot where interruption is safe and never where it is not, and investigate any line you cannot explain.

Instance family selection is a cost decision: match the family to the resource that binds first.

Self-Hosted Stateful Services

Operate Kafka, PostgreSQL and Redis in-cluster, covering persistence, replication, failover, upgrades, and backups you have actually restored from.

Rehearse the restore and record how long it took.

Security Posture

IAM and workload identity, migration away from static credentials, secret management, web application firewall rules, and closing the gaps you find.

Credential rotation and least privilege are ongoing work, not a one-time project.

AI Infrastructure (Growth Path)

Within the first year, take on the infrastructure serving AI workloads: multi-provider LLM gateway and routing, token and cost attribution, rate-limit-aware capacity planning, LLM tracing with Langfuse, vector databases such as pgvector and Qdrant, and self-hosted embedding models including GPU nodes on Kubernetes.

This is inference operations, not model training.

AI-Assisted Engineering Discipline

Use Claude, Cursor, and similar tools day to day for infrastructure code, scripts, and pipelines.

Set the team standard for safe use, review, and validation of AI-generated infrastructure before it ships.

Requirements:

Hands-on Production Ownership of Self-Managed Kubernetes (Mandatory)

Must have personally operated a production Kubernetes estate with operational responsibility including oncall, incident response, and upgrade ownership.

You understand why a cluster ends up over-provisioned and how to fix it.

Managed-platform-only experience, or Kubernetes limited to deploying into a cluster someone else runs, does not qualify.

5+ Years of Overall Engineering Experience

With at least 3 years in DevOps, SRE, or platform engineering.

This is not an ML science role.

A strong infrastructure background with genuine appetite for AI infrastructure is exactly the profile we want.

Proven Ability to Learn an Unfamiliar Technology to Production Depth

We are hiring for trajectory as much as for current tooling, so this carries real weight.

Be ready to walk us through something you picked up from scratch and then owned in production: what you got wrong in the first attempt, how you found out, and what you would do differently.

A candidate with a shorter tool list and a strong record of learning will be preferred over a longer list learned only at the surface.

Self-Hosted Stateful Services in Production

One or more of Kafka, PostgreSQL, Redis, or Elasticsearch operated by you, not by a managed service.

Backups, restores, failover, and version upgrades.

This matters more than any other line here, because almost everything we run, we run ourselves.

Infrastructure as Code Depth

Terraform in anger, including modules, state management, and recovering from drift.

Docker and image optimisation.

AWS at Depth

EKS, EC2, VPC, IAM, S3, RDS or Aurora, and load balancing.

You can read a bill and explain where the money went.

Networking Depth

VPC and subnet design, NAT and egress paths, load balancer behaviour, DNS, TLS, and Kubernetes networking.

Able to reason about address exhaustion and routing limits before they are hit rather than after.

Observability Depth

Production experience with Prometheus, Grafana, and a log or trace backend.

Comfortable instrumenting with OpenTelemetry.

Able to define alerts that are actionable and to resist the cardinality that makes a metrics system collapse.

CI/CD and Deployment Automation

Strong with GitHub Actions or GitLab CI, including self-hosted runners and short-lived cloud credentials.

Experience making deploys and rollbacks safe and routine.

Cost Management for Cloud Infrastructure

Demonstrated ownership of a cloud bill: right-sizing, reserved capacity or savings plans, Spot strategy, and tracing an anomaly to its cause.

Reliability Engineering

Comfortable defining SLOs and being accountable for them.

Experience with graceful shutdown, connection draining, disruption budgets, and long-lived connections such as WebSockets that autoscaling can otherwise sever.

Nice to Have:

• arm64 and Graviton estates
• eBPF networking with Cilium
• container runtime isolation such as gVisor, Kata, or Firecracker
• Kafka operations including partition and consumer-group management
• service mesh with Istio
• GPU workloads on Kubernetes
• hands-on familiarity with LLM observability tooling such as Langfuse or LangSmith
• India data-protection and residency requirements under the DPDP Act
• AWS certifications

Please Apply - https://zrec.in/7EYKe?source=CareerSite

About Us

Infra360 Solutions is a services company specializing in Cloud, DevSecOps, Security, and Observability solutions. We help technology companies adapt DevOps culture in their organization by focusing on long-term DevOps roadmap. We focus on identifying technical and cultural issues in the journey of successfully implementing the DevOps practices in the organization and work with respective teams to fix issues to increase overall productivity. We also do training sessions for the developers and make them realize the importance of DevOps. We provide these services - DevOps, DevSecOps, FinOps, Cost Optimizations, CI/CD, Observability, Cloud Security, Containerization, Cloud Migration, Site Reliability, Performance Optimizations, SIEM and SecOps, Serverless automation, Well-Architected Review, MLOps, Governance, Risk & Compliance. We do assessments of technology architecture, security, governance, compliance, and DevOps maturity model for any technology company and help them optimize their cloud cost, streamline their technology architecture, and set up processes to improve the availability and reliability of their website and applications. We set up tools for monitoring, logging, and observability. We focus on bringing the DevOps culture to the organization to improve its efficiency and delivery.

Job Description

Job Title:             Senior DevOps Engineer / SRE

Department:       Technology

Location:             Gurgaon

Work Mode:         On-site

Working Hours:   10 AM - 7 PM 

Terms:                 Permanent

Experience:      4-6 years

Education:           B.Tech/MCA

Notice Period:     Immediately

​

About Us

At Infra360.io, we are a next-generation cloud consulting and services company committed to delivering comprehensive, 360-degree solutions for cloud, infrastructure, DevOps, and security. We partner with clients to transform and optimize their technology landscape, ensuring resilience, scalability, cost efficiency and innovation.

Our core services include Cloud Strategy, Site Reliability Engineering (SRE), DevOps, Cloud Security Posture Management (CSPM), and related Managed Services. We specialize in driving operational excellence across multi-cloud environments, helping businesses achieve their goals with agility and reliability.

We thrive on ownership, collaboration, problem-solving, and excellence, fostering an environment where innovation and continuous learning are at the forefront. Join us as we expand and redefine what’s possible in cloud technology and infrastructure.

Role Summary

We are seeking a Senior DevOps Engineer (SRE) to manage and optimize large-scale, mission-critical production systems. The ideal candidate will have a strong problem-solving mindset, extensive experience in troubleshooting, and expertise in scaling, automating, and enhancing system reliability. This role requires hands-on proficiency in tools like Kubernetes, Terraform, CI/CD, and cloud platforms (AWS, GCP, Azure), along with scripting skills in Python or Go. The candidate will drive observability and monitoring initiatives using tools like Prometheus, Grafana, and APM solutions (Datadog, New Relic, OpenTelemetry).

Strong communication, incident management skills, and a collaborative approach are essential. Experience in team leadership and multi-client engagement is a plus.

Ideal Candidate Profile

• Solid 4-6 years of experience as an SRE and DevOps with a proven track record of handling large-scale production environments
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Strong Hands-on experience with managing Large Scale Production Systems
• Strong Production Troubleshooting Skills and handling high-pressure situations.
• Strong Experience with Databases (PostgreSQL, MongoDB, ElasticSearch, Kafka)
• Worked on making production systems more Scalable, Highly Available and Fault-tolerant
• Hands-on experience with ELK or other logging and observability tools
• Hands-on experience with Prometheus, Grafana & Alertmanager and on-call processes like Pagerduty
• Problem-Solving Mindset
• Strong with skills - K8s, Terraform, Helm, ArgoCD, AWS/GCP/Azure etc
• Good with Python/Go Scripting Automation
• Strong with fundamentals like DNS, Networking, Linux
• Experience with APM tools like - Newrelic, Datadog, OpenTelemetry
• Good experience with Incident Response, Incident Management, Writing detailed RCAs
• Experience with Applications best practices in making apps more reliable and fault-tolerant
• Strong leadership skills and the ability to mentor team members and provide guidance on best practices.
• Able to manage multiple clients and take ownership of client issues.
• Experience with Git and coding best practices

Good to have

• Team-leading Experience
• Multiple Client Handling
• Requirements gathering from clients
• Good Communication

Key Responsibilities

1. Design and Development:
2. Architect, design, and develop high-quality, scalable, and secure cloud-based software solutions.
3. Collaborate with product and engineering teams to translate business requirements into technical specifications.
4. Write clean, maintainable, and efficient code, following best practices and coding standards.
5. Cloud Infrastructure:
6. Develop and optimise cloud-native applications, leveraging cloud services like AWS, Azure, or Google Cloud Platform (GCP).
7. Implement and manage CI/CD pipelines for automated deployment and testing.
8. Ensure the security, reliability, and performance of cloud infrastructure.
9. Technical Leadership:
10. Mentor and guide junior engineers, providing technical leadership and fostering a collaborative team environment.
11. Participate in code reviews, ensuring adherence to best practices and high-quality code delivery.
12. Lead technical discussions and contribute to architectural decisions.
13. Problem Solving and Troubleshooting:
14. Identify, diagnose, and resolve complex software and infrastructure issues.
15. Perform root cause analysis for production incidents and implement preventative measures.
16. Continuous Improvement:
17. Stay up-to-date with the latest industry trends, tools, and technologies in cloud computing and software engineering.
18. Contribute to the continuous improvement of development processes, tools, and methodologies.
19. Drive innovation by experimenting with new technologies and solutions to enhance the platform.
20. Collaboration:
21. Work closely with DevOps, QA, and other teams to ensure smooth integration and delivery of software releases.
22. Communicate effectively with stakeholders, including technical and non-technical team members.
23. Client Interaction & Management: 
24. Will serve as a direct point of contact for multiple clients.
25. Able to handle the unique technical needs and challenges of two or more clients concurrently. 
26. Involve both direct interaction with clients and internal team coordination.
27. Production Systems Management: 
28. Must have extensive experience in managing, monitoring, and debugging production environments. 
29. Will work on troubleshooting complex issues and ensure that production systems are running smoothly with minimal downtime.

(Candidates from Service based Companies apply-Looking for automation(shell or python scripting))

SHIFT- Shift time either US East coast or west coast (2:30 PM to 10:30 PM India time or 5 to 2 am india time)

Exp- 5 to 8 years

Salary- Upto 25 LPA

Hyderabad based candidates preferred!

Immediate joiners would be preferred!!

Role Objective:

• Ability to identify processes where efficiency could be improved via automation
• Ability to research, prototype, iterate and test automation solutions
• Good Technical understanding of Cloud service offering, with a sound appreciation of the associated business processes.
• Ability to build & maintain a strong working relationship with other Technical teams using the agile methodology (internal and external), Infrastructure Partners and Service Engagement Managers.
• Ability to shape and co-ordinate delivery of key initiatives to deliver improvements in stability
• Good understanding of the cost of the e2e service provision, and delivery of associated savings.
• Knowledge of web security principals
• Strong Linux experience – comfortable working from command line
• Some networking knowledge (routing, DNS)
• Knowledge of HA and DR concepts and experience implementing them
• Working with team to analyse and design infrastructure with 99.99% up-time.

Qualifications:

• Infrastructure automation through DevOps scripting (Eg Python, Ruby, PowerShell, Java, shell) or previous software development experience
• Experience in building and managing production cloud environments from the ground up.
• Hands-on, working experience with primary AWS services (EC2, VPC, RDS, Route53, S3)
• Knowledge on repository management (GitHub, SVN)
• Solid understanding of web application architecture and RDBMS (SQL Server preferred).
• Experience with IT compliance and risk management requirements is a bonus. (Eg Security, Privacy, HIPAA, SOX, etc)
• Strong logical, analytical and problem-solving skills with excellent communication skills.
• Should have degree in computer science, MIS, engineering or equivalent with 5+ years of experience.
• Should be willing to work in rotational shifts (including the nights)

Perks and benefits:

• Health & Wellness
• Paid time off
• Learning at work
• Fun at work
• Night shift allowance
• Comp off
• Pick and drop facility available to certain distance

1. Develop and Deploy Software:
1. Architect and create an effective build and release process using industry best practices and tools
2. Create and manage build scripts to deploy software in a multi-cloud environment
3. Look for opportunities to automate as much of the deployment process as possible to provide for repeatability, auditability, scalability and build in process enforcement
2. Manage Release Schedule:
1. Act as a “gate keeper” for all releases into production
2. Work closely with business stakeholders, development managers and developers to prepare a release schedule
3. Help prioritize deployment requests for version upgrades, patches and hot-fixes
3. Continuous Delivery of Software:
1. Implement Continuous Integration (CI) practices to drive development teams to implement smaller changes and commit code to the version control repo frequently
2. Implement Continuous Development (CD) practices that automates deployment of the application to several environments – Dev, Test and Production
3. Implement Continuous Testing (functional and non-functional) to execute tests in the CI/CD pipeline
4. Manage Version Control:
1. Define and implement branching policies to efficiently manage source-code
2. Implement business rules as a part of source control standards
5. Resolve Software Issues:
1. Assist technical support and development teams to troubleshoot issues and identify areas that need improvement
2. Address deployment related issues
6. Maintain Release Documentation:
1. Maintain release notes (features available in stable versions and known issues) and other documents for both internal and external end users