Ziploan - DevOps Engineer

Position: DevOps Engineer / Senior DevOps Engineer

Experience: 3 to 6 Years

Key Skills: AWS, Terraform, Docker, Kubernetes, DevSecOps pipeline

Job Description:

• AWS Infrastructure: Architect, deploy, and manage AWS services like EC2, S3, RDS, Lambda, SageMaker, API Gateway, and VPC.
• Networking: Proficient in subnetting, endpoints, NACL, security groups, VPC flow logs, and routing.
• API Management: Design and manage secure, scalable APIs using AWS API Gateway.
• CI/CD Pipelines: Build and maintain CI/CD pipelines with AWS CodePipeline, CodeBuild, and CodeDeploy.
• Automation & IaC: Use Terraform and CloudFormation for automating infrastructure management.
• Containerization & Kubernetes: Expertise in Docker, Kubernetes, and managing containerized deployments.
• Monitoring & Logging: Implement monitoring with AWS CloudWatch, CloudTrail, and other tools.
• Security: Apply AWS security best practices using IAM, KMS, Secrets Manager, and GuardDuty.
• Cost Management: Monitor and optimize AWS usage and costs.
• Collaboration: Partner with development, QA, and operations teams to enhance productivity and system reliability.

Senior MLOps Engineer

LLM Operations, Observability & Eval Infrastructure

📍 Mumbai (On-site) | Full-time | 5-7 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 MLOps Engineer for a dedicated client engagement focused on building an AI-powered application builder platform. The platform consumes LLMs at scale through provider APIs.

This role owns the operational discipline around production LLM consumption - increasingly called LLMOps - covering observability, evaluation infrastructure, model lifecycle, cost operations, prompt deployment, and agent run reliability.

The mandatory requirement is hands-on production experience operating LLM-backed systems, with a strong DevOps or SRE foundation. This is not a model training or ML science role.

The work is making the system around the AI engineer's designs observable, controlled, reliable, and economically accountable. You will pair daily with the Senior AI Engineer, who designs prompts, evals, and agent behaviour - you operationalise those systems for production.

A typical week includes a tracing audit on a degraded agent run, an eval pipeline build for a new model release, a cost attribution review, and a staged prompt rollout.

Responsibilities:

Observability and Tracing

Build and own end-to-end tracing for agent runs: every prompt, response, tool call, token count, latency, and cost, linked to user session and project.

Stand up and operate LLM observability tooling (Langfuse, LangSmith, Braintrust, or Arize Phoenix).

Make debugging a single bad agent run among thousands a routine workflow through searchable traces, failure taxonomies, and dashboards segmented by task type.

Evaluation Infrastructure as a Production System

Operationalise the eval suite designed by the Senior AI Engineer: automated execution in CI on every prompt or model change, with results stored and trended over time.

Implement regression gates that block quality-degrading changes from shipping.

Build production sampling to continuously score a sample of real agent runs and catch quality drift that offline evals miss.

Model Lifecycle Management

Pin model versions, never "latest".

Own the upgrade process: run the eval suite against new model releases and manage eval-gated migrations.

Maintain fallback chains across providers for graceful degradation or queueing during outages.

Track provider deprecation schedules and plan migrations ahead of forced cutoffs.

Cost Operations

Implement per-user and per-task cost attribution - token spend is the platform's largest variable cost and requires the same rigour as cloud cost management.

Set up budget alerts and anomaly detection so a single user or bug cannot burn significant spend overnight.

Monitor prompt cache hit rates and quantify savings.

Manage capacity planning around provider rate limits, including quota negotiation and throughput tiering.

Prompt and Configuration Deployment

Treat prompts as production artifacts: version control for prompts and agent configurations, staged rollout infrastructure (deploy a prompt change to a percentage of traffic before full rollout), A/B testing infrastructure, instant rollback, and audit history covering which prompt version served which user and when.

Reliability Engineering for Agent Runs

Agent runs are long, stateful, and failure-prone.

Own retry and resume semantics so a run that fails mid-way does not restart from scratch.

Implement timeouts and circuit breakers on provider calls, dead-letter handling for failed runs, and queue and concurrency management for agent workloads.

SLO Ownership and Incident Response

Define and track SLOs for agent run latency and completion rates.

Lead incident response when SLOs are breached.

Write postmortems.

Surface reliability risks proactively before they reach users.

Safety and Compliance Operations

Run the moderation pipeline (prompt and output classification) in production.

Monitor for abuse patterns and own incident response when the agent misbehaves at scale.

Maintain audit logs and implement data retention and residency policies for prompts and generated code as enterprise requirements emerge.

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 LLM-backed systems in operation (mandatory).

Must have personally shipped and operated at least one LLM-powered system in production, with operational responsibility including oncall, incident response, and reliability ownership.

Alternatively: strong DevOps or SRE background with demonstrated hands-on familiarity with LLMOps tooling (Langfuse, LangSmith, Braintrust, Arize, or equivalent).

POCs and lab work do not qualify.

5+ years of overall engineering experience

With at least 2 years in DevOps, SRE, platform engineering, or LLM operations roles.

This is not an ML science role.

A DevOps or SRE background with a substantive pivot into LLMOps is a strong qualification.

Observability and Tracing Depth

Production experience with LLM observability tooling - Langfuse, LangSmith, Braintrust, or Arize Phoenix.

Comfortable instrumenting with OpenTelemetry, Prometheus, and Grafana.

Able to build and search trace pipelines, define failure taxonomies, and surface quality signals from production traffic.

CI/CD and Quality Gate Experience

Strong with GitHub Actions or GitLab CI.

Experience building automated quality gates: eval-gated pipelines, regression enforcement, or coverage gates that block degrading changes from shipping.

Cost Management and Attribution for Usage-Based Services

Experience owning cost attribution for cloud API spend or equivalent.

Comfortable with budget alerts, anomaly detection, and per-user or per-task cost breakdowns.

Reliability Engineering for Long-Running, Stateful Workloads

Experience with queues, retry patterns, idempotency, and failure recovery on asynchronous or multi-step workloads.

Comfortable defining SLOs and being accountable for them on production systems.

Multi-Provider API Management

Familiarity with LLM provider rate limits, version pinning, fallback chains, and quota management across OpenAI, Anthropic, Google, or equivalent.

Infrastructure as Code and Deployment Automation

Hands-on with Terraform or Pulumi and Docker.

AWS working knowledge (EC2, S3, IAM, EKS or ECS).

Strong with CI/CD for deploying services and configuration changes safely.

Nice to Have

• Experience with prompt A/B testing or staged rollout infrastructure
• Workflow orchestration (BullMQ, Temporal, Celery)
• Content moderation pipeline experience
• Data residency and compliance requirements for AI systems
• Kubernetes (EKS) in production
• AWS certifications

About MyOperator

MyOperator is a Business AI Operator, a category leader that unifies WhatsApp, Calls, and AI-powered chat & voice bots into one intelligent business communication platform. Unlike fragmented communication tools, MyOperator combines automation, intelligence, and workflow integration to help businesses run WhatsApp campaigns, manage calls, deploy AI chatbots, and track performance — all from a single, no-code platform. Trusted by 12,000+ brands including Amazon, Domino's, Apollo, and Razorpay, MyOperator enables faster responses, higher resolution rates, and scalable customer engagement — without fragmented tools or increased headcount.

Job Summary

We are looking for a skilled and motivated DevOps Engineer with 3+ years of hands-on experience in AWS cloud infrastructure, CI/CD automation, and Kubernetes-based deployments. The ideal candidate will have strong expertise in Infrastructure as Code, containerization, monitoring, and automation, and will play a key role in ensuring high availability, scalability, and security of production systems.

Key Responsibilities

• Design, deploy, manage, and maintain AWS cloud infrastructure, including EC2, RDS, OpenSearch, VPC, S3, ALB, API Gateway, Lambda, SNS, and SQS.
• Build, manage, and operate Kubernetes (EKS) clusters and containerized workloads.
• Containerize applications using Docker and manage deployments with Helm charts
• Develop and maintain CI/CD pipelines using Jenkins for automated build and deployment processes
• Provision and manage infrastructure using Terraform (Infrastructure as Code)
• Implement and manage monitoring, logging, and alerting solutions using Prometheus and Grafana
• Write and maintain Python scripts for automation, monitoring, and operational tasks
• Ensure high availability, scalability, performance, and cost optimization of cloud resources
• Implement and follow security best practices across AWS and Kubernetes environments
• Troubleshoot production issues, perform root cause analysis, and support incident resolution
• Collaborate closely with development and QA teams to streamline deployment and release processes

Required Skills & Qualifications

• 3+ years of hands-on experience as a DevOps Engineer or Cloud Engineer.
• Strong experience with AWS services, including:
• EC2, RDS, OpenSearch, VPC, S3
• Application Load Balancer (ALB), API Gateway, Lambda
• SNS and SQS.
• Hands-on experience with AWS EKS (Kubernetes)
• Strong knowledge of Docker and Helm charts
• Experience with Terraform for infrastructure provisioning and management
• Solid experience building and managing CI/CD pipelines using Jenkins
• Practical experience with Prometheus and Grafana for monitoring and alerting
• Proficiency in Python scripting for automation and operational tasks
• Good understanding of Linux systems, networking concepts, and cloud security
• Strong problem-solving and troubleshooting skills

Good to Have (Preferred Skills)

• Exposure to GitOps practices
• Experience managing multi-environment setups (Dev, QA, UAT, Production)
• Knowledge of cloud cost optimization techniques
• Understanding of Kubernetes security best practices
• Experience with log aggregation tools (e.g., ELK/OpenSearch stack)

Language Preference

• Fluency in English is mandatory.
• Fluency in Hindi is preferred.

About us:

HappyFox is a software-as-a-service (SaaS) support platform. We offer an enterprise-grade help desk ticketing system and intuitively designed live chat software.

We serve over 12,000 companies in 70+ countries. HappyFox is used by companies that span across education, media, e-commerce, retail, information technology, manufacturing, non-profit, government and many other verticals that have an internal or external support function.

To know more, Visit! - https://www.happyfox.com/

Responsibilities

• Build and scale production infrastructure in AWS for the HappyFox platform and its products.
• Research, Build/Implement systems, services and tooling to improve uptime, reliability and maintainability of our backend infrastructure. And to meet our internal SLOs and customer-facing SLAs.
• Implement consistent observability, deployment and IaC setups
• Lead incident management and actively respond to escalations/incidents in the production environment from customers and the support team.
• Hire/Mentor other Infrastructure engineers and review their work to continuously ship improvements to production infrastructure and its tooling.
• Build and manage development infrastructure, and CI/CD pipelines for our teams to ship & test code faster.
• Lead infrastructure security audits

Requirements

• At least 7 years of experience in handling/building Production environments in AWS.
• At least 3 years of programming experience in building API/backend services for customer-facing applications in production.
• Proficient in managing/patching servers with Unix-based operating systems like Ubuntu Linux.
• Proficient in writing automation scripts or building infrastructure tools using Python/Ruby/Bash/Golang
• Experience in deploying and managing production Python/NodeJS/Golang applications to AWS EC2, ECS or EKS.
• Experience in security hardening of infrastructure, systems and services.
• Proficient in containerised environments such as Docker, Docker Compose, Kubernetes
• Experience in setting up and managing test/staging environments, and CI/CD pipelines.
• Experience in IaC tools such as Terraform or AWS CDK
• Exposure/Experience in setting up or managing Cloudflare, Qualys and other related tools
• Passion for making systems reliable, maintainable, scalable and secure.
• Excellent verbal and written communication skills to address, escalate and express technical ideas clearly
• Bonus points – Hands-on experience with Nginx, Postgres, Postfix, Redis or Mongo systems.

Specific responsibilities commensurate with experience and include:

• Ability to react quickly and effectively to identify and resolve issues that heavily impact CI/CD system (immediate mitigation of impact, long-term resolution including strategies for risk mitigation/monitoring/alert for proactive resolution of potential future occurrences)
• Design, develop, unit test, and implement build automation scripts including environment configuration validation processes
• Automate and improve development process by evaluation and introduction of new tools and scripts, and manage their life cycle and validation
• Determine branching strategy and maintain branches for various components, products, and product lines
• Come up with solutions to open-ended problems that focus on workflow improvements for the Software department
• Address issues with well-defined requirements efficiently; come up with short-term and long-term solutions and staged deployment strategies
• Self-driven-- takes action to move tickets from start to completion with minimal oversight
• Ability to communicate with and consider perspectives of stakeholders including but not limited to: IT, software development, verification
• Ability to break down a problem into smaller components and solve them in a logical, controlled, clearly explainable approach
• Lead the creation and maintenance of a pre-production environment as a testbed for build process improvements and changes before deployment to the production environment
• Gather metrics via direct input, data based on analysis of developer working habits analysis and pain points to assess current state and areas requiring further improvement
• Define chain of communication and immediate paths of action in the case of a build fault state
• Ability to work within constraints of the internal network without access to commercial cloud solutions
• Create metrics that define ‘efficiency’ and ‘reliability’ in measurable terms, and track them
• Perform static code and security analysis
• Design and execute unit tests and perform code coverage analysis
• Able to work in Agile development team environment

• Bachelor’s degree (or higher) in Electrical Engineering, Computer Engineering, Computer Science or equivalent
• 6+ years (minimum) experience handling Build, Release, and Deployment of software on Windows and/or Linux environments (on-premise)
• Experience with the development and deployment of CM processes and tools
• Build automation for .NET using TeamCity (Jenkins is an asset)
• Scripting languages: Windows batch scripting, Powershell, Ant/NAnt
• Source control systems usage, branching strategies, and workflow (Git preferred, Subversion)
• 6+ years of hands-on programming experience with C# and .NET (both Framework and Core)
• Troubleshooting and debugging-- what information to gather when there are issues with CI/CD system, and how to gather it (i.e., analyzing network communication? Windows crash dumps, java logs, etc.)
• 6+ years (minimum) in web/desktop application software development experience
• Excellent problem solving, critical and analytical thinking
• Strong team player who understands SDLC and QA methodologies
• A professional, results-oriented individual with a high degree of self-motivation
• Excellent written and verbal communication skills and the ability to coordinate work/activities with multiple software/IT teams
• Working with virtual machines and build management on virtual machines (VMware preferred).
• Managing configurations for multiple build environments
• OS administration and scripting experience (Windows is a must, Linux desired)
• Experience with test automation tools (NUnit, customer inhouse frameworks) and strategies is an asset
• Creation and maintenance of monitoring and alert systems (Zabbix)
• Familiarity with databases (SQL-based) - create, modify, optimize (via script)
• Data and metrics gathering, aggregation, and reporting
• Experience with work management and documentation tools: JIRA and Confluence

• 5+ years hands-on experience with designing, deploying and managing core AWS services and infrastructure
• Proficiency in scripting using Bash, Python, Ruby, Groovy, or similar languages 
• Experience in source control management, specifically with Git
• Hands-on experience in Unix/Linux and bash scripting
• Experience building, managing Helm-based build and release CI-CD pipelines for Kubernetes platforms (EKS, Openshift, GKE) 
• Strong experience with orchestration and config management tools such as Terraform, Ansible or Cloudformation  
• Ability to debug, analyze issues leveraging tools like App Dynamics, New Relic and Sumologic 
• Knowledge of Agile Methodologies and principles 
• Good writing and documentation skills
• Strong collaborator with the ability to work well with core teammates and our colleagues across STS

Required Skills and Experience 

• 4+ years of relevant experience with DevOps tools Jenkins, Ansible, Chef etc
• 4+ years of experience in continuous integration/deployment and software tools development experience with Python and shell scripts etc
• Building and running Docker images and deployment on Amazon ECS
• Working with AWS services (EC2, S3, ELB, VPC, RDS, Cloudwatch, ECS, ECR, EKS)
• Knowledge and experience working with container technologies such as Docker and Amazon ECS, EKS, Kubernetes
• Experience with source code and configuration management tools such as Git, Bitbucket, and Maven
• Ability to work with and support Linux environments (Ubuntu, Amazon Linux, CentOS)
• Knowledge and experience in cloud orchestration tools such as AWS Cloudformation/Terraform etc
• Experience with implementing "infrastructure as code", “pipeline as code” and "security as code" to enable continuous integration and delivery
• Understanding of IAM, RBAC, NACLs, and KMS
• Good communication skills

Good to have:

• Strong understanding of security concepts, methodologies and apply them such as SSH, public key encryption, access credentials, certificates etc.
• Knowledge of database administration such as MongoDB.
• Knowledge of maintaining and using tools such as Jira, Bitbucket, Confluence.
• Work with Leads and Architects in designing and implementation of technical infrastructure, platform, and tools to support modern best practices and facilitate the efficiency of our development teams through automation, CI/CD pipelines, and ease of access and performance.
• Establish and promote DevOps thinking, guidelines, best practices, and standards.
• Contribute to architectural discussions, Agile software development process improvement, and DevOps best practices.