DevOps Engineer

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.

Job Purpose and Impact

The DevOps Engineer is a key position to strengthen the security automation capabilities which have been identified as a critical area for growth and specialization within Global IT’s scope. As part of the Cyber Intelligence Operation’s DevOps Team, you will be helping shape our automation efforts by building, maintaining and supporting our security infrastructure.

Key Accountabilities

• Collaborate with internal and external partners to understand and evaluate business requirements.
• Implement modern engineering practices to ensure product quality.
• Provide designs, prototypes and implementations incorporating software engineering best practices, tools and monitoring according to industry standards.
• Write well-designed, testable and efficient code using full-stack engineering capability.
• Integrate software components into a fully functional software system.
• Independently solve moderately complex issues with minimal supervision, while escalating more complex issues to appropriate staff.
• Proficiency in at least one configuration management or orchestration tool, such as Ansible.
• Experience with cloud monitoring and logging services.

Qualifications

Minimum Qualifications

• Bachelor's degree in a related field or equivalent exp
• Knowledge of public cloud services & application programming interfaces
• Working exp with continuous integration and delivery practices

Preferred Qualifications

• 3-5 years of relevant exp whether in IT, IS, or software development
• Exp in:
•  Code repositories such as Git
• Scripting languages (Python & PowerShell)
• Using Windows, Linux, Unix, and mobile platforms within cloud services such as AWS
• Cloud infrastructure as a service (IaaS) / platform as a service (PaaS), microservices, Docker containers, Kubernetes, Terraform, Jenkins
• Databases such as Postgres, SQL, Elastic

 3-5 years of experience in DevOps, systems administration, or software engineering roles.

 B. Tech. in computer science or related field from top tier engineering colleges.

 Strong technical skills in software development, systems administration, and cloud infrastructure management.

 Experience with infrastructure-as-code tools such as Terra form or Cloud Formation.

 Experience with containerization technologies such as Dockers and Kubernetes.

 Experience with cloud providers such as AWS or Azure.

 Experience with scripting languages such as Bash or Python.

 Strong problem-solving and analytical skills.

 Strong communication and collaboration skills

Implementation Engineer

Implementation Engineer Duties and Responsibilities

• Understanding requirements from internal consumers about program functionality.
• Perform UAT tests on application with help of test cases and prepare documents for same and coordinate with team to resolve all issues within required timeframe and inform management of any delays.
• Collaborate with development team to design new programs for all client implementation activities and manage all communication with department to resolve all issues and assist implementation analyst to manage all production data.
• Perform research on all client issues and document all findings and implement all technical activities with help of JIRA.
• Assist internal teams to monitor all software implementation lifecycle and assist to track appropriate customization to all software for clients.
• Train technical staff on all OS and software issues and identify all issues in processes and provide solutions for same. Train other team members on processes, procedures, API functionality, and development specifications.
• Supervise/support crossed-functional teams to design, test and deploy to achieve on-time project completion.
• Implement, configure, and debug MySQL, JAVA, Redis, PHP, Node, ActiveMQ setups.
• Monitor and troubleshoot infrastructure utilizing SYSLOG, SNMP and other monitoring software.
• Install, configure, monitor and upgrade applications during installation/upgrade activities.
• Assisting team to identify network issue and help them with respective resolutions.
• Utilize JIRA for issue reporting, status, activity planning, tracking and updating project defects and tasks.
• Managing JIRA and tracking tickets to closure and follow-ups with team members.
• Troubleshoot software issues
• Provide on-call support as necessary

Implementation Engineer Requirements and Qualifications

• Bachelor’s degree in computer science, software engineering, or a related field
• Experience working with
• Linux & Windows Operating system
• Working on shell and bat scripts
• SIP/ISUP based solutions
• deploying / debugging Java, C++ based solutions.
• MySQL to install, backup, update and retrieve data
• Front-end or back-end software development for LINUX
• database management and security a plus
• Very good debugging and analytical skills
• Good Communication skills

About Us

We have grown over 1400% in revenues in the last year.

Interface.ai provides an Intelligent Virtual Assistant (IVA) to FIs to automate calls and customer inquiries across multiple channels and engage their customers with financial insights and upsell/cross-sell.

Our IVA is transforming financial institutions’ call centers from a cost to a revenue center.

Our core technology is built 100% in-house with several breakthroughs in Natural Language Understanding. Our parser is built based on zero-shot learning that helps us to launch industry-specific IVA that can achieve over 90% accuracy on Day-1. 

We are 45 people strong with employees spread across India and US locations. Many of them come from ML teams at Apple, Microsoft, and Salesforce in the US along with enterprise architects with over 20+ years of experience building large-scale systems. Our India team consists of people from ISB, IIMs, and many who have been previously part of early-stage startups. 

We are a fully remote team.

Founders come from Banking and Enterprise Technology backgrounds with previous experience scaling companies from scratch to $50M+ in revenues.

As a Site Reliability Engineer you will be in charge of:

• Designing, analyzing and troubleshooting large-scale distributed systems
• Engaging in cross-functional team discussions on design, deployment, operation, and maintenance,  in a fast-moving, collaborative set up
• Building automation scripts to validate the stability, scalability, and reliability of interface.ai’s products & services as well as enhance interface.ai’s employees’ productivity
• Debugging and optimizing code and automating routine tasks
• Troubleshoot and diagnose issues (hardware or software), propose and implement solutions to ensure they occur with reduced frequency
• Perform the periodic on-call duty to handle security, availability, and reliability of interface.ai’s products 
• You will follow and write good code and solid engineering practices

You can be a great fit if you are :

1. Extremely self motivated
2. Ability to learn quickly
3. Growth Mindset (read this if you don't know what it means - https://www.amazon.com/Mindset-Psychology-Carol-S-Dweck/dp/0345472322" target="_blank">link)
4. Emotional Maturity (read this if you don't know what it means - https://medium.com/@krisgage/15-signs-of-emotional-maturity-38b1a2ab9766" target="_blank">link)
5. Passionate about the possibilities at the intersection of AI + Banking
6. Worked in a startup of 5 to 30 employees
7. Developer with a strong interest in systems Design. You will be building, maintaining, and scaling our cloud infrastructure through software tooling and automation. 
8. 4-8 years of industry experience developing and troubleshooting large-scale infrastructure on the cloud
9. Have a solid understanding of system availability, latency, and performance
10. Strong programming skills in at least one major programming language and the ability to learn new languages as needed  
11. Strong System/network debugging skills
12. Experience with management/automation tools such as Terraform/Puppet/Chef/SALT
13. Experience with setting up production-level monitoring and telemetry
14. Expertise in Container management & AWS
15. Experience with kubernetes is a plus
16. Experience building CI/CD pipelines
17. Experience working with Web sockets, Redis, Postgres, Elastic search, Logstash
18. Experience working in an agile team environment and proficient understanding of code versioning tools, such as Git.
19. Ability to effectively articulate technical challenges and solutions.
20. Proactive outlook for ways to make our systems more reliable