AWS DevOps+MLOps Engineer

Amura’s Vision 

We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.

Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades.

Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture.

These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.

We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence. 

Role Overview 

We are looking for a highly skilled Senior DevOps Engineer (AI-Native Infrastructure & Platform Engineering) with deep expertise in AWS cloud infrastructure, automation, AI infrastructure operations, and modern DevOps/SRE practices.

This role goes beyond traditional DevOps and requires a seasoned specialist capable of building and operating AI-ready infrastructure platforms that support high-throughput APIs, LLM/AI workloads, GPU-based compute, data-intensive systems, real-time inference pipelines, and scalable ML platforms.

You will be responsible for architecting, automating, securing, and optimizing highly scalable and cost-efficient cloud environments that enable high-velocity engineering and AI teams. This is an ideal position for someone who combines technical ownership, an automation-first mindset, and a passion for developer productivity and platform reliability. 

Key Responsibilities 

Cloud Infrastructure & Platform Engineering (AWS) 

• Architect, deploy, and manage highly scalable and secure infrastructure on AWS. Design cloud platforms supporting AI/ML workloads, data pipelines, real-time APIs, and high-concurrency backend systems.
• Hands-on expertise with key AWS services including EC2, ECS/EKS, Lambda, RDS, DynamoDB, S3, VPC, CloudFront, IAM, CloudWatch, and GPU-enabled instances.
• Build and maintain Infrastructure-as-Code (IaC) using Terraform, CloudFormation, or AWS CDK.
• Design multi-AZ and multi-region architectures for high availability and disaster recovery (HA/DR).
• Build reusable platform templates and shared infrastructure modules. 

AI/ML Infrastructure & MLOps 

• Build and maintain infrastructure for LLM applications, AI inference workloads, model serving platforms, vector databases, and feature stores.
• Support GPU-based workloads and optimize compute/storage usage.
• Enable scalable deployment patterns for AI applications using Kubernetes/EKS. Collaborate with Data Science and ML Engineering teams on model deployment, training/tuning of models, CI/CD for ML systems, experiment environments, and reproducibility.
• Support orchestration and deployment of AI workflows and inference services while implementing observability and reliability for AI pipelines. 

CI/CD, Automation & Developer Productivity 

• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
• Automate deployments, environment provisioning, and release workflows.
• Build self-service developer platforms, preview environments, and reusable deployment workflows to improve developer productivity.
• Implement automated patching, scaling, backups, cleanup workflows, and drift detection. 

Containers, Kubernetes & Platform Reliability

• Manage Docker-based environments, containerized applications, and optimize workloads using Kubernetes (EKS) or ECS/Fargate.
• Manage autoscaling, cluster health, node pools, ingress, service mesh, and workload isolation.
• Optimize infrastructure for performance, resilience, and cost-efficiency.
• Implement progressive deployment strategies including blue/green, canary, and rolling deployments. 

Observability, Incident Response & SRE Practices

• Implement observability stacks using CloudWatch, Prometheus, Grafana, ELK, Datadog, OpenTelemetry, or New Relic.
• Build actionable dashboards and intelligent alerting systems while defining and tracking SLIs, SLOs, and SLAs.
• Lead incident response, root cause analysis, and blameless postmortems to reduce operational toil and improve MTTR.

FinOps, Cost Governance & Security

• Continuously monitor and optimize cloud costs (compute utilization, storage lifecycle, GPU usage, and data transfer) using AWS Cost Explorer, Budgets, Trusted Advisor, CloudHealth, or Kubecost.
• Implement AWS security best practices for IAM, VPCs, security groups, NACLs, encryption, and manage secrets using KMS, SSM Parameter Store, or Vault.
• Build secure CI/CD pipelines with automated security checks, least-privilege access, audit logging, and ensure compliance readiness for ISO 27001, SOC2, and GDPR.

Collaboration, Leadership & Platform Culture

• Work closely with engineering, AI/ML, QA, product, and operations teams to drive a DevOps, SRE, GitOps, and automation-first culture.
• Mentor junior DevOps and Platform Engineers while creating and maintaining detailed runbooks, architecture diagrams, and platform documentation.

Skills & Qualifications

Must-Have:

• 7+ years of experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure Engineering.
• Strong expertise in AWS cloud architecture, services, and deep understanding of Kubernetes (EKS), containers, and cloud-native systems.
• Strong Infrastructure-as-Code expertise using Terraform, CloudFormation, or CDK. Strong Linux administration, networking, DNS, routing, and load balancing knowledge. Strong scripting/programming experience in Python, Bash, or Go (preferred). Experience with CI/CD automation, GitOps workflows, and observability platforms supporting scalable production systems.

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Here are answers to some questions you may have

Where is your office?

Chennai (Velachery)

Work Model

Work from Office – because great stories are built in person!

Do you have an online presence?

https://amura.ai (we are @AmuraHealth on all social media)

 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  

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: Linux & 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.

Example Responsibilities:

• Build and optimize model serving infrastructure with a focus on inference latency and cost optimization
• Architect efficient inference pipelines that balance latency, throughput, and cost across various acceleration options
• Develop monitoring and observability solutions for ML systems
• Collaborate with ML Engineers to establish best practices for optimized model deployment
• Implement cost-efficient, enterprise-scale solutions
• Collaborate in a cross-functional, distributed team for continuous system improvement
• Work with MLEs, QA Engineers, and DevOps Engineers
• Evaluate and implement new technologies and tools
• Contribute to architectural decisions for distributed ML systems

Experience and Qualifications:

• 5+ years of experience in software engineering with Python
• Experience with ML frameworks, particularly PyTorch
• Experience optimizing ML models with hardware acceleration (AWS Neuron , ONNX, TensorRT)
• Experience with AWS ML services and hardware-accelerated instances (Sagemaker, Inferentia,Trainium)
• Proven experience building and operating AWS serverless architectures
• Deep understanding of event-driven processing patterns, SQS/SNS and serverless caching solutions
• Experience with containerization using Docker and orchestration tools
• Strong knowledge of RESTful API design and implementation
• Proficiency in writing good quality & secure code and be familiar with static code analysis tools
• Excellent analytical, conceptual and communication skills in spoken and written English
• Experience applying Computer Science fundamentals in algorithm design, problem solving, and complexity analysis

Great to have Experience and Qualifications:

• Experience with any of the following: model compilation and quantization, performance profiling and benchmarking ML inference systems
• Experience working in regulated industries with strict compliance requirements for cloud-native solutions

Key Responsibilities

• Automate application deployments from Bitbucket to servers using CI/CD pipelines.
• Design and manage scalable, highly available AWS infrastructure.
• Implement Auto Scaling, ELB, and Route 53 for traffic management and high availability.
• Work with AWS services including IAM, RDS, DynamoDB, EC2, and other cloud services.
• Build and manage Docker containers and server images.
• Deploy and manage applications using Kubernetes.
• Implement Infrastructure as Code using Terraform, CloudFormation, or Ansible.
• Develop automation scripts using Python and Bash.
• Implement monitoring and logging using tools such as Prometheus, Grafana, and ELK.
• Integrate security and compliance practices into CI/CD pipelines.
• Optimize infrastructure for security, scalability, performance, and cost.

Required Skills

• 3+ years of experience in DevOps or a similar role.
• Strong knowledge of AWS beyond EC2.
• Hands-on experience with Jenkins or similar CI/CD tools.
• Experience with Docker and Kubernetes.
• Good understanding of Terraform/IaC and automation.
• Proficiency in Python and/or Bash scripting.
• Knowledge of DevSecOps, security, and compliance best practices.
• Strong troubleshooting and problem-solving skills.