Full Stack Developer

Job Title : IBM Sterling Integrator Developer

Experience : 3 to 5 Years

Locations : Hyderabad, Bangalore, Mumbai, Gurgaon, Chennai, Pune

Employment Type : Full-Time

Job Description :

We are looking for a skilled IBM Sterling Integrator Developer with 3–5 years of experience to join our team across multiple locations.

The ideal candidate should have strong expertise in IBM Sterling and integration, along with scripting and database proficiency.

Key Responsibilities :

• Develop, configure, and maintain IBM Sterling Integrator solutions.
• Design and implement integration solutions using IBM Sterling.
• Collaborate with cross-functional teams to gather requirements and provide solutions.
• Work with custom languages and scripting to enhance and automate integration processes.
• Ensure optimal performance and security of integration systems.

Must-Have Skills :

• Hands-on experience with IBM Sterling Integrator and associated integration tools.
• Proficiency in at least one custom scripting language.
• Strong command over Shell scripting, Python, and SQL (mandatory).
• Good understanding of EDI standards and protocols is a plus.

Interview Process :

• 2 Rounds of Technical Interviews.

Additional Information :

• Open to candidates from Hyderabad, Bangalore, Mumbai, Gurgaon, Chennai, and Pune.

Role: Senior Platform Engineer (GCP Cloud)

Experience Level: 3 to 6 Years

Work location: Mumbai

Mode : Hybrid

Role & Responsibilities:

• Build automation software for cloud platforms and applications
• Drive Infrastructure as Code (IaC) adoption
• Design self-service, self-healing monitoring and alerting tools
• Automate CI/CD pipelines (Git, Jenkins, SonarQube, Docker)
• Build Kubernetes container platforms
• Introduce new cloud technologies for business innovation

Requirements:

• Hands-on experience with GCP Cloud
• Knowledge of cloud services (compute, storage, network, messaging)
• IaC tools experience (Terraform/CloudFormation)
• SQL & NoSQL databases (Postgres, Cassandra)
• Automation tools (Puppet/Chef/Ansible)
• Strong Linux administration skills
• Programming: Bash/Python/Java/Scala
• CI/CD pipeline expertise (Jenkins, Git, Maven)
• Multi-region deployment experience
• Agile/Scrum/DevOps methodology

Role: Full-Time, Long-Term Required: Docker, GCP, CI/CD Preferred: Experience with ML pipelines

OVERVIEW

We are seeking a DevOps engineer to join as a core member of our technical team. This is a long-term position for someone who wants to own infrastructure and deployment for a production machine learning system. You will ensure our prediction pipeline runs reliably, deploys smoothly, and scales as needed.

The ideal candidate thinks about failure modes obsessively, automates everything possible, and builds systems that run without constant attention.

CORE TECHNICAL REQUIREMENTS

Docker (Required): Deep experience with containerization. Efficient Dockerfiles, layer caching, multi-stage builds, debugging container issues. Experience with Docker Compose for local development.

Google Cloud Platform (Required): Strong GCP experience: Cloud Run for serverless containers, Compute Engine for VMs, Artifact Registry for images, Cloud Storage, IAM. You can navigate the console but prefer scripting everything.

CI/CD (Required): Build and maintain deployment pipelines. GitHub Actions required. You automate testing, building, pushing, and deploying. You understand the difference between continuous integration and continuous deployment.

Linux Administration (Required): Comfortable on the command line. SSH, diagnose problems, manage services, read logs, fix things. Bash scripting is second nature.

PostgreSQL (Required): Database administration basics—backups, monitoring, connection management, basic performance tuning. Not a DBA, but comfortable keeping a production database healthy.

Infrastructure as Code (Preferred): Terraform, Pulumi, or similar. Infrastructure should be versioned, reviewed, and reproducible—not clicked together in a console.

WHAT YOU WILL OWN

Deployment Pipeline: Maintaining and improving deployment scripts and CI/CD workflows. Code moves from commit to production reliably with appropriate testing gates.

Cloud Run Services: Managing deployments for model fitting, data cleansing, and signal discovery services. Monitor health, optimize cold starts, handle scaling.

VM Infrastructure: PostgreSQL and Streamlit on GCP VMs. Instance management, updates, backups, security.

Container Registry: Managing images in GitHub Container Registry and Google Artifact Registry. Cleanup policies, versioning, access control.

Monitoring and Alerting: Building observability. Logging, metrics, health checks, alerting. Know when things break before users tell us.

Environment Management: Configuration across local and production. Secrets management. Environment parity where it matters.

WHAT SUCCESS LOOKS LIKE

Deployments are boring—no drama, no surprises. Systems recover automatically from transient failures. Engineers deploy with confidence. Infrastructure changes are versioned and reproducible. Costs are reasonable and resources scale appropriately.

ENGINEERING STANDARDS

Automation First: If you do something twice, automate it. Manual processes are bugs waiting to happen.

Documentation: Runbooks, architecture diagrams, deployment guides. The next person can understand and operate the system.

Security Mindset: Secrets never in code. Least-privilege access. You think about attack surfaces.

Reliability Focus: Design for failure. Backups are tested. Recovery procedures exist and work.

CURRENT ENVIRONMENT

GCP (Cloud Run, Compute Engine, Artifact Registry, Cloud Storage), Docker, Docker Compose, GitHub Actions, PostgreSQL 16, Bash deployment scripts with Python wrapper.

WHAT WE ARE LOOKING FOR

Ownership Mentality: You see a problem, you fix it. You do not wait for assignment.

Calm Under Pressure: When production breaks, you diagnose methodically.

Communication: You explain infrastructure decisions to non-infrastructure people. You document what you build.

Long-Term Thinking: You build systems maintained for years, not quick fixes creating tech debt.

EDUCATION

University degree in Computer Science, Engineering, or related field preferred. Equivalent demonstrated expertise also considered.

TO APPLY

Include: (1) CV/resume, (2) Brief description of infrastructure you built or maintained, (3) Links to relevant work if available, (4) Availability and timezone.

Salesforce DevOps/Release Engineer

Resource type - Salesforce DevOps/Release Engineer

Experience - 5 to 8 years

Norms - PF & UAN mandatory

Resource Availability - Immediate or Joining time in less than 15 days

Job - Remote

Shift timings - UK timing (1pm to 10 pm or 2pm to 11pm)

Required Experience:

• 5–6 years of hands-on experience in Salesforce DevOps, release engineering, or deployment management.
• Strong expertise in Salesforce deployment processes, including CI/CD pipelines.
• Significant hands-on experience with at least two of the following tools: Gearset, Copado,Flosum.
• Solid understanding of Salesforce architecture, metadata, and development lifecycle.
• Familiarity with version control systems (e.g., Git) and agile methodologies

Key Responsibilities:

• Design, implement, and manage CI/CD pipelines for Salesforce deployments using Gearset, Copado, or Flosum.
• Automate and optimize deployment processes to ensure efficient, reliable, and repeatable releases across Salesforce environments.
• Collaborate with development, QA, and operations teams to gather requirements and ensurealignment of deployment strategies.
• Monitor, troubleshoot, and resolve deployment and release issues.
• Maintain documentation for deployment processes and provide training on best practices.
• Stay updated on the latest Salesforce DevOps tools, features, and best practices.

Technical Skills:

• Deployment ToolsHands-on with Gearset, Copado, Flosum for Salesforce deployments
• CI/CDBuilding and maintaining pipelines, automation, and release management
• Version ControlProficiency with Git and related workflows
• Salesforce PlatformUnderstanding of metadata, SFDX, and environment management
• Scripting
• Familiarity with scripting (e.g., Shell, Python) for automation (preferred)
• Communication
• Strong written and verbal communication skills

Preferred Qualifications:

Bachelor’s degree in Computer Science, Information Technology, or related field.

Certifications:

Salesforce certifications (e.g., Salesforce Administrator, Platform Developer I/II) are a plus.

Experience with additional DevOps tools (Jenkins, GitLab, Azure DevOps) is beneficial.

Experience with Salesforce DX and deployment strategies for large-scale orgs. 

Skills 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

• Candidate should have good Platform experience on Azure with Terraform.
• The devops engineer  needs to help developers, create the Pipelines and K8s Deployment Manifests.
• Good to have experience on migrating data from (AWS) to Azure. 
• To manage/automate infrastructure automatically using Terraforms. Jenkins is the key CI/CD tool which we uses and it will be used to run these Terraforms.
• VMs to be provisioned on Azure Cloud and managed.
• Good hands on experience of Networking on Cloud is required.
• Ability to setup Database on VM as well as managed DB and Proper set up of cloud hosted microservices needs to be done to communicate with the db services.
• Kubernetes, Storage, KeyValult, Networking(load balancing and routing) and VMs are the key infrastructure expertise which are essential. 
• Requirement is  to administer Kubernetes cluster end to end. (Application deployment, managing namespaces, load balancing, policy setup, using blue-green/canary deployment models etc).
• The experience in AWS is desirable 
• Python experience is optional however Power shell is mandatory
• Know-how on the use of GitHub