AWS DevOps+MLOps Engineer

• Bachelor’s degree in computer science, Data Science, Information Systems, or a related field  
• 8-10 years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering  
• Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure  
• Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn  

Job Title: Java AWS Kubernetes DevOps AI/ML

Experience: 8–10 Years

The candidate should have at least 1 year of experience in AI/ML and hands-on experience with the below technologies:

Java

AWS

Kubernetes

DevOps

AI/ML

MongoDB / PostgreSQL

Key-Value Caching

Vector Databases – ChromaDB / Pgvector

 The Role 

As a **DevOps Engineer** you'll own the infrastructure and delivery backbone that 

keeps our platform running as we grow. You'll build the CI/CD, cloud infrastructure, and 

observability that let a small, fast-moving team ship confidently — and you'll keep our AI and 

data workloads reliable and affordable at scale. 

This is a hands-on role with real ownership: you won't be maintaining someone else's setup, 

you'll be shaping ours. You'll work closely with the backend, AI/ML, and data teams to make 

deployment boring, incidents rare, and scaling a non-event. --- 

What You'll Own 

**CI/CD & developer experience** 

- Build and maintain fast, reliable CI/CD pipelines so engineers ship multiple times a day with 

confidence. - Make the path from commit to production simple, safe, and repeatable, with sensible 

automated testing, rollbacks, and release controls. 

**Cloud infrastructure & IaC** - Own our cloud infrastructure (AWS/GCP) end to end, managed as code (Terraform or 

similar) — no click-ops. - Design for scale and cost-efficiency as store and conversation volumes grow. 

**Containers & orchestration** - Run our services on containers/Kubernetes: deployments, autoscaling, networking, and 

resource management. - Support the specific needs of AI/ML workloads, including GPU-backed inference and batch 

processing for the speech pipeline. 

**Reliability & observability (SRE)** - Own uptime, performance, and incident response — monitoring, logging, tracing, alerting, 

on-call, and blameless postmortems. - Define and defend SLOs; keep the platform dependable as it scales across clients. 

**Data & pipeline infrastructure** - Support the infrastructure behind large-scale, edge-to-cloud data movement and 

processing (audio ingestion, ASR/AI pipelines, analytics). - Keep data workloads reliable, performant, and cost-aware. 

**Security & compliance** - Bake security into the platform: secrets management, IAM/least-privilege, encryption in 

transit and at rest, network hardening, and vulnerability management. - Support compliance readiness (including India's DPDP Act and enterprise-client security 

requirements) for a product that handles sensitive customer conversations. 

**Cost & scale** - Own cloud cost visibility and optimization; make scaling decisions that balance reliability 

and spend. --- 

What You'll Bring - 6+ years in DevOps, SRE, platform, or infrastructure engineering, running production 

systems at meaningful scale. - Strong hands-on experience with a major cloud provider (**AWS or Azure or GCP**) and 

Infrastructure-as-Code (**Terraform** or equivalent). - Solid experience with **containers and Kubernetes** in production. - Experience building and owning **CI/CD** pipelines (e.g. GitHub Actions, GitLab CI, 

Jenkins, Argo, or similar). 

- Comfort with a scripting/automation language (Python, Go, or Bash) and a strong 

automation-first mindset. - Real experience with **observability** (Prometheus/Grafana, ELK, Datadog, 

OpenTelemetry, or similar) and running incident response / on-call. - A security-conscious approach — secrets, IAM, encryption, and least-privilege as defaults. - Startup temperament: ownership, pragmatism, and a bias to automate and ship. - Based in or willing to relocate to Bangalore, and up for an onsite/hybrid, in-person team. 

Bonus Points - Experience running **ML/AI or GPU workloads** in production (inference serving, batch 

pipelines, model deployment). - Experience with data-intensive infrastructure — streaming/queues (Kafka, SQS), data 

pipelines, or large object/audio storage. - Exposure to **edge devices / IoT fleets**, OTA updates, or high-volume device-to-cloud 

ingestion. - Experience with compliance/security frameworks (SOC 2, ISO 27001, DPDP). - FinOps / cloud cost-optimization experience. - Early-stage startup experience. --- 

Why Join - Own infrastructure that's already live with leading retail brands and growing fast — real 

scale, real impact. - Work across genuinely interesting workloads: speech AI, GPU inference, large-scale data, 

and edge-to-cloud ingestion. - Small team, high ownership, direct line to engineering leadership — your decisions ship. - Build the platform foundation of a category-defining product from an

Greetings!

Hiring For Large Product Based Company!

Role- Mlops Engineer

Experience- 8-12 years

Location- Pune, Nagpur

JD-

• 8-10 years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering  
• Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure  

Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn  

Key Responsibilities:

• Develop and deploy machine learning, deep learning, and NLP models for various business use cases.
• Build end-to-end ML pipelines including data preprocessing, feature engineering, training, evaluation, and production deployment.
• Optimize model performance and ensure scalability in production environments.
• Work closely with data scientists, product teams, and engineers to translate business requirements into AI solutions.
• Conduct data analysis to identify trends and insights.
• Implement MLOps practices for versioning, monitoring, and automating ML workflows.
• Research and evaluate new AI/ML techniques, tools, and frameworks.
• Document system architecture, model design, and development processes.

Required Skills:

• Strong programming skills in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras).
• Hands-on experience in building and deploying, finetuning ML/DL models in production.
• Good understanding of machine learning algorithms, neural networks, NLP, and computer vision.
• Experience with REST APIs, Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure).
• Working knowledge of MLOps tools such as MLflow, Airflow, DVC, or Kubeflow.
• Familiarity with data pipelines and big data technologies (Spark, Hadoop) is a plus.
• Strong analytical skills and ability to work with large datasets.
• Excellent communication and problem-solving abilities.
• Experience in deploying models using cloud services (AWS Sagemaker, GCP Vertex AI, etc.).
• Experience in LLM fine-tuning or Generative AI, Voice AI, is an added advantage.

Educational Qualification:

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Machine Learning, IT, from IIT/NIT colleges strongly preferred

Company Overview:

Planview is hiring a DevOps Engineer in Bengaluru, India to support Planview SaaS applications across the product line. You will work in a global, collaborative team — owning CI/CD pipelines, cloud infrastructure, and automation to keep deployments fast and systems reliable.

Responsibilities

• Build and maintain CI/CD pipelines in Jenkins for reliable, fast delivery.
• Manage containerized workloads on Docker and ECS — task definitions, services, and clusters.
• Provision and manage AWS infrastructure using Terraform (CloudFormation a plus).
• Automate configuration and deployment tasks using Python (Ansible a plus).
• Set up and maintain monitoring and alerting via New Relic (CloudWatch, Datadog, or Prometheus/Grafana a plus).
• Write Shell and Python scripts to automate operations and reduce manual work.
• Manage Git workflows — branching, merge strategies, and pull request reviews.
• Administer and support MSSQL databases underpinning the product line — backups, restores, and basic performance troubleshooting.
• Troubleshoot deployment, performance, and infrastructure issues with development teams.
• Participate in on-call rotations and drive incident response.
• Continuously improve infrastructure resilience and deployment speed.
• Apply AI-assisted engineering tools (e.g., GitHub Copilot, Claude Code) to speed up IaC authoring, pipeline debugging, and day-to-day scripting.

Qualifications

Must-Have Skills

• Experience: 4–6 years of experience in DevOps, SRE, or Infrastructure Engineering.
• OS: Windows administration (systemd, package management, log analysis).
• Cloud: AWS (Active Directory, ECS, EC2, CloudFront, S3, VPC, IAM, RDS, Lambda basics).
• Source Control: Git — branching, merge/rebase, PR reviews.
• CI/CD (Jenkins): Pipeline creation and basic Groovy scripting.
• Containerization (Docker + ECS): Task definitions, services, and clusters.
• IaC: Terraform.
• Monitoring: New Relic.
• Scripting: Bash and Python scripting for automation.
• Networking Basics: DNS, load balancers, security groups, VPNs.
• Logging: ELK stack / CloudWatch Logs.
• Database: MSSQL administration — backups, restores, basic performance troubleshooting.
• Infrastructure Automation: Hands-on experience automating infrastructure provisioning, configuration, and deployment end-to-end.
• AI-Assisted Engineering: Comfortable working with AI coding/DevOps assistants (e.g., GitHub Copilot, Claude Code) for IaC generation, scripting, and troubleshooting — verified via a mandatory AI proficiency assessment during interviews.

Nice-to-Have Skills

•     Configuration Management: Ansible.

•     Additional IaC: CloudFormation.

•     Architecture: Knowledge of microservices architecture.

•     Cloudflare: DNS, CDN, WAF.

•     Artifact Repositories: Nexus, JFrog Artifactory, ECR.

•     Other CI/CD Tools: GitHub Actions.

•     AWS cost optimization / FinOps awareness.

•     Datadog, CloudWatch, or Prometheus/Grafana.

•     AIOps: Exposure to AI-driven anomaly detection, root-cause analysis, or incident triage (e.g., Dynatrace Davis AI, Datadog Bits AI, Harness AIDA).

•     Database Basics: RDS backups, restores, performance tuning.

Job Description:

Pre-requisite skills required for a DevOps Engineer role include:

• 6+yrs exp in DevOps
• Experience working on Linux based infrastructure
• knowledge in AWS, docker, CI/CD tools
• Hands on exp in Python/shell scripting language
• hands on exp in AWS and Azure
• Work exp in Docker, Terraform, Ansible, Kubernetes, LINUX
• Excellent understanding of Ruby, Python, Perl, and Java
• Configuration and managing databases such as MySQL, Mongo
• Excellent troubleshooting
• Working knowledge of various tools, open-source technologies, and cloud services

As a DevOps Engineer at YOYO, you'll own the infrastructure and delivery backbone that keeps our platform running as we grow. You'll build the CI/CD, cloud infrastructure, and observability that let a small, fast-moving team ship confidently and you'll keep our AI and data workloads reliable and affordable at scale. This is a hands-on role with real ownership: you won't be maintaining someone else's setup, you'll be shaping ours. You'll work closely with the backend, AI/ML, and data teams to make deployment boring, incidents rare, and scaling a non-event.

If you are Interested DM me on LinkedIn - Saquib Mundagnur

 What You'll Own

CI/CD & developer experience - Build and maintain fast, reliable CI/CD pipelines so engineers ship multiple times a day with confidence. - Make the path from commit to production simple, safe, and repeatable, with sensible automated testing, rollbacks, and release controls.Cloud infrastructure & IaC - Own our cloud infrastructure (AWS/GCP) end to end, managed as code (Terraform or similar) — no click-ops. - Design for scale and cost-efficiency as store and conversation volumes grow.

Containers & orchestration - Run our services on containers/Kubernetes: deployments, autoscaling, networking, and resource management. - Support the specific needs of AI/ML workloads, including GPU-backed inference and batch processing for the speech pipeline.

Reliability & observability (SRE) - Own uptime, performance, and incident response — monitoring, logging, tracing, alerting, on-call, and blameless postmortems. - Define and defend SLOs; keep the platform dependable as it scales across clients.

Data & pipeline infrastructure - Support the infrastructure behind large-scale, edge-to-cloud data movement and processing (audio ingestion, ASR/AI pipelines, analytics). - Keep data workloads reliable, performant, and cost-aware.

Security & compliance - Bake security into the platform: secrets management, IAM/least-privilege, encryption in transit and at rest, network hardening, and vulnerability management. - Support compliance readiness (including India's DPDP Act and enterprise-client security requirements) for a product that handles sensitive customer conversations.

Cost & scale - Own cloud cost visibility and optimization; make scaling decisions that balance reliability and spend. 

What You'll Bring - 6+ years in DevOps, SRE, platform, or infrastructure engineering, running production systems at meaningful scale.

- Strong hands-on experience with a major cloud provider (**AWS or Azure or GCP**) and Infrastructure-as-Code (**Terraform** or equivalent).

- Solid experience with **containers and Kubernetes** in production. - Experience building and owning **CI/CD** pipelines (e.g. GitHub Actions, GitLab CI, Jenkins, Argo, or similar).

- Comfort with a scripting/automation language (Python, Go, or Bash) and a strong automation-first mindset.

- Real experience with **observability** (Prometheus/Grafana, ELK, Datadog, OpenTelemetry, or similar) and running incident response / on-call.

- A security-conscious approach — secrets, IAM, encryption, and least-privilege as defaults. - Startup temperament: ownership, pragmatism, and a bias to automate and ship. - Based in or willing to relocate to Bangalore, and up for an onsite/hybrid, in-person team

Job Summary :

We are looking for a proactive and skilled DevOps Engineer to join our team and play a key role in building, managing, and scaling infrastructure for high-performance systems. The ideal candidate will have hands-on experience with Kubernetes, Docker, Python scripting, cloud platforms, and DevOps practices around CI/CD, monitoring, and incident response.

Key Responsibilities :

- Design, build, and maintain scalable, reliable, and secure infrastructure on cloud platforms such as AWS.

- Implement Infrastructure as Code (IaC) using tools like Terraform, Cloud Formation, or similar.

- Manage Kubernetes clusters, configure namespaces, services, deployments, and auto scaling. CI/CD & Release Management

- Build and optimize CI/CD pipelines for automated testing, building, and deployment of services.

- Collaborate with developers to ensure smooth and frequent deployments to production.

- Manage versioning and rollback strategies for critical deployments.

- Containerization & Orchestration using Kubernetes.

- Containerize applications using Docker, and manage them using Kubernetes.

- Write automation scripts using Python or Shell for infrastructure tasks, monitoring, and deployment flows.

- Develop utilities and tools to enhance operational efficiency and reliability.

- Monitoring & Incident Management

- Analyze system performance and implement infrastructure scaling strategies based on load and usage trends.

- Optimize application and system performance through proactive monitoring and configuration tuning.

Desired Skills and Experience :

- Experience Required - 6+ yrs.

- Hands-on experience on cloud services like AWS, EKS etc.

- Ability to design a good cloud solution.

- Strong Linux troubleshooting, Shell Scripting, Kubernetes, Docker, Ansible, Jenkins Skills.

- Design and implement the CI/CD pipeline following the best industry practices using open-source tools.

- Use knowledge and research to constantly modernize our applications and infrastructure stacks.

- Be a team player and strong problem-solver to work with a diverse team.

- Having good communication skills.

Location: Bangalore preferred / Hybrid as applicable

Experience: 3+ years

Education: B.E/B.Tech in Computer Science, Engineering or a related technical discipline

Salary: Above market standards, flexible for the right candidate

Career growth: Long-term opportunity with potential to lead DevOps architecture and cloud platform operations

About FrontM

FrontM builds software platforms for frontline workforces operating in remote and low-connectivity environments, with a strong focus on the maritime industry. The platform supports communication, collaboration, healthcare, learning, welfare and operational workflows across mobile, web, kiosk and connected device environments.

The platform runs across cloud infrastructure, constrained networks and specialised customer environments, requiring reliable DevOps practices, strong observability, secure architecture and careful operational discipline.

Role Summary

As a Senior DevOps Engineer, you will take ownership of FrontM’s AWS cloud infrastructure, CI/CD pipelines, platform reliability and technical operations. You will work closely with the VP of Delivery, CTO and CEO to maintain secure, scalable and high-availability infrastructure for FrontM’s production systems.

This role requires strong hands-on DevOps experience, broad AWS knowledge, Kubernetes experience and the ability to troubleshoot complex networking and production issues across multi-domain SaaS environments.

Key Responsibilities

Cloud Infrastructure & DevOps Architecture (≈45%)

· Own, maintain and improve AWS cloud infrastructure for FrontM platforms

· Create and maintain Terraform scripts for infrastructure deployment and management

· Manage Kubernetes workloads deployed within AWS EKS

· Support multi-zone AWS infrastructure design for availability, resilience and scale

· Maintain AWS services including Route 53, EC2, API Gateway, VPC, VPN, AWS Cognito, ElastiCache, DynamoDB and Lambda

· Contribute to DevOps architecture planning in line with FrontM’s platform roadmap

CI/CD, Operations & Platform Reliability (≈35%)

· Build, maintain and improve CI/CD pipelines for backend and platform services

· Oversee technical operations with hands-on administration, monitoring and release support

· Ensure continuous server uptime, stability, performance and maintainability

· Debug, respond to and restore system outages in production and staging environments

· Improve observability across infrastructure and applications, including migration from Elastic stack to logz.io

· Support backend stability, scale and performance across Node.js, Java and related services

Security, Networking & Production Support (≈20%)

· Maintain AWS security configurations, access controls and monitoring practices

· Support complex networking requirements across multi-domain SaaS implementations

· Troubleshoot network, infrastructure and access issues with internal teams and customer-side users

· Work with backend teams to support API integrations and infrastructure abstractions for complex requirements

· Document operational procedures, incident findings and technical support steps clearly

Required Technical Skills

Cloud Infrastructure & AWS

· Strong hands-on experience with AWS infrastructure and cloud operations

· Experience with Route 53, EC2, API Gateway, VPC, VPN, AWS Cognito, ElastiCache, DynamoDB and Lambda

· Experience with AWS security setup, monitoring and multi-zone infrastructure

· Ability to manage infrastructure using Terraform

Kubernetes, CI/CD & Observability

· Strong experience with Kubernetes, preferably AWS EKS

· Extensive CI/CD and DevOps experience

· Experience with infrastructure observability and application monitoring tools

· Ability to diagnose production bottlenecks, server failures and performance issues

Backend, Networking & SaaS Operations

· Experience supporting Node.js, Java and backend system procedures for stability and scale

· Good understanding of APIs, integrations and backend service dependencies

· Experience with complex networking and multi-domain SaaS implementations

· Ability to troubleshoot technical issues with non-technical end users

Nice to Have

· Experience with MongoDB clusters in MongoDB Atlas

Personal Attributes

· Strong ownership mindset for uptime, reliability and production stability

· Practical problem-solving approach with the ability to act quickly during incidents

· Clear written and spoken communication in English

· Ability to work independently and coordinate with senior management when required

· Comfortable working in fast-moving engineering teams

· Attention to detail in security, monitoring, documentation and operational processes

Why join FrontM?

Long-Term Career Growth

Opportunity to work on cloud infrastructure used by global maritime and remote workforce customers, with scope to grow into DevOps architecture and platform leadership roles.

Engineering Challenges That Matter

Work on infrastructure that supports applications used in remote, low-bandwidth and operationally demanding environments.

Broad Technical Ownership

Take responsibility across cloud infrastructure, Kubernetes, CI/CD, observability, networking, security and production reliability.

Apply now

Join a team focused on building reliable software infrastructure for real-world use cases and contribute to systems used across the global maritime workforce.