Systems 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)

Very strong infra engineer to administer Linux based VMs (and few Windows VMs as well).

Must have strong knowledge and hands-on on docker, Kubernetes

Must be good at monitoring (AppDynamics, Prometheus, Grafana) and logging (Splunk)

Develop automation scripts using Shell and Python. Must have good knowledge in Ansible.

Should be good at optimize/finetune server configurations.

 Should be good in troubleshoot issues and fix them.

About the Role

We are hiring Staff / Principal Engineers to take full, hands-on ownership of Blitzy's most critical production-grade systems and to deliver high-leverage features that materially improve customer outcomes and engineering velocity. This is the most senior individual contributor role at the company today.

This is not a Senior-plus role, an architecture-only role, or a promotion-track role. We are looking for someone who has already operated at Principal / Staff+ scope in a highly technical environment and expects to spend their time writing, reviewing, and shipping production code.

This role is 100% hands-on. Leverage comes from system ownership, execution quality, and durable technical decisions — not people management or process.

Responsibilities

• Own mission-critical production systems end-to-end, ensuring correctness, scalability, performance, reliability, and operational excellence.
• Design, build, and ship high-impact backend systems and features that improve product reliability, performance, and customer value.
• Architect scalable services and cloud infrastructure using technologies such as Python, REST, gRPC, Kubernetes, and Terraform.
• Identify and resolve complex technical bottlenecks that limit engineering quality, system performance, or organizational velocity.
• Build and operate LLM-powered systems and validation loops that evaluate correctness, consistency, durability, and production performance.
• Design and evolve data architectures incorporating relational, NoSQL, graph, and vector databases to support complex enterprise applications and semantic retrieval.
• Modernize and improve complex enterprise systems while balancing reliability, maintainability, scalability, and delivery speed.
• Set and uphold engineering quality standards through hands-on technical leadership, sound technical judgment, and ownership of long-term technical decisions.

Qualifications

• Direct experience with Python as a primary programming language, backend frameworks, and microservices architectures.
• Expertise in REST and gRPC, with proficiency in Node.js and JavaScript.
• Proficiency in GCP, along with experience using at least one additional cloud platform such as AWS or Azure.
• Advanced knowledge of Kubernetes and Terraform in production environments.
• Experience operating highly available production systems, including monitoring, scalability, reliability, performance optimization, and operational tooling.
• Strong knowledge of SQL and NoSQL databases, including PostgreSQL, MySQL, MongoDB, Cassandra, or DynamoDB.
• Familiarity with graph databases such as Neo4j and vector databases or embedding infrastructure for semantic search and retrieval.
• Hands-on experience building and operating LLM-powered systems in production, including evaluation, validation, regression testing, tracing, and failure analysis.
• Working knowledge of LangSmith or comparable LLM observability and evaluation tools; familiarity with OpenAI, Anthropic, or similar model providers is a plus.
• Ability to contribute across the full stack, with a strong understanding of frontend architecture and the ability to debug, design, and ship across frontend, backend, infrastructure, and AI systems.
• Understanding of large-scale enterprise software systems, including architecture, integration, deployment, modernization, and long-term maintainability.
• Proven track record of operating at Staff+, Principal Engineer, or equivalent level, independently driving complex technical initiatives and delivering high-impact outcomes with minimal supervision.

Blitzy is a Cambridge, MA based AI software development platform on a mission to revolutionize the software development life cycle by autonomously building custom software to unlock the next industrial revolution. We're transforming how enterprises build software, turning enterprise requirements into enterprise grade code with an agentic software development platform that can autonomously execute 80% of the quantum of software development work. We're backed by multiple tier 1 investors, and have proven success as founders of previous start-ups.

Our Culture

Who we are:

Led by two pioneering co-founders we are one of the fastest growing companies in the U.S., creating our own category of enterprise autonomous software development. We automate thousands of hours of software development for our customers, which includes strong representation within the Fortune 500.

How we work:

• We move Blitzy Fast: Time is both our company’s and our clients’ most precious asset. We move quickly and decisively to innovate internally and deliver exceptional software externally.
• Championship Mindset: We operate like a professional sports team. We win as a team by holding ourselves and each other to high standards, collaborating in-person, and remaining focused on the mission.
• Passion for Invention: We’re pushing the frontier of what’s possible, requiring constant innovation and iteration.
• We Work for the Customer: We focus on delivering outsized value to the customers we work with and expanding those relationships into deep, meaningful partnerships.
• We believe in being ‘everyday athletes’: taking care of ourselves so we can bring our best minds to work. We promote great sleep, movement, and restorative activities for 

Blitzy is an equal opportunity employer committed to building a diverse and inclusive team. We believe different perspectives make us stronger.

We are seeking a highly skilled and experienced DevOps Engineer to join our development team.

Years of experience needed: 8+ Yrs

Required Skills

Strong experience with GitLab, TeamCity, Terraform, Kubernetes and Docker

Proficiency in various deployment strategies and CI/CD pipeline setups

Solid understanding of Linux administration and Windows IIS.

Advanced scripting skills in bash and PowerShell

Hands-on experience with Google Cloud Platform (GCP) services, particularly GKE, GCS, GCE, Cloud SQL, and load balancers

Familiarity with Autosys for job scheduling and automation

Excellent problem-solving and troubleshooting skills

Ability to work independently and collaboratively in a fast-paced environment

• • Strong communication and interpersonal skills.

Job Description: AI Engineer – GenAI Platform Automation

Experience: 10+ Years

Location: Remote – Pan India

Employment Type: Haparz Payroll

Work Mode: Remote

Notice Period: Immediate / Short Notice Preferred

About the Role

We are looking for a senior AI Engineer – GenAI Platform Automation to lead automation initiatives across enterprise Generative AI, Data Science, Data Engineering, and Analytics platforms.

The role focuses on building scalable, secure, and self-service automation capabilities across infrastructure provisioning, CI/CD, cloud environments, AI workload deployment, governance, observability, and operational excellence. The ideal candidate will have strong hands-on experience in platform engineering, cloud automation, DevOps, Infrastructure-as-Code, Python, and enterprise GenAI ecosystems.

Key Responsibilities

• Lead end-to-end automation initiatives for enterprise GenAI, Data Science, Data Engineering, Metadata, Data Quality, Event Streaming, and Analytics platforms.
• Design self-service automation for infrastructure provisioning, environment onboarding, deployment, governance, monitoring, and operational workflows.
• Build automation capabilities supporting the AI lifecycle, including experimentation, model training, deployment, inference, observability, and lifecycle management.
• Develop scalable Infrastructure-as-Code solutions using Terraform and cloud-native automation frameworks.
• Design and maintain enterprise CI/CD pipelines, automated testing, deployment, and release processes using modern DevOps toolchains.
• Automate Kubernetes, containers, serverless, and distributed computing environments in collaboration with cloud and platform engineering teams.
• Develop automation solutions for GenAI and Agentic AI applications, including MCP-enabled services, API integrations, workflow automation, and event-driven architectures.
• Implement observability, monitoring, logging, tracing, alerting, automated remediation, and reliability engineering practices.
• Work with architecture, security, governance, engineering, and business teams to ensure enterprise standards and compliance requirements are met.
• Conduct technical design reviews, automation assessments, code reviews, and establish engineering best practices.
• Provide technical leadership and mentorship to engineering teams adopting automation-first and platform engineering practices.

What We’re Looking For

• 10+ years of hands-on experience in platform engineering, automation engineering, cloud engineering, DevOps, or distributed systems.
• Strong experience building enterprise self-service platforms supporting AI/ML, Data Science, Data Engineering, or Advanced Analytics workloads.
• Strong expertise in automation frameworks, CI/CD, DevOps, Infrastructure-as-Code, and software delivery lifecycle automation.
• Hands-on experience with Terraform and cloud-native infrastructure automation.
• Strong experience with Python for automation, orchestration, scripting, tooling, and platform engineering.
• Experience with Bitbucket, Bamboo, Jira, Confluence, or similar enterprise DevOps toolchains.
• Experience working with Kubernetes, containers, serverless platforms, YARN, and distributed processing environments.
• Knowledge of Generative AI and Agentic AI architectures, MCP frameworks, APIs, workflow automation, and enterprise AI platforms.
• Experience with event-driven architectures and technologies such as Kafka and streaming platforms.
• Strong understanding of cloud engineering, networking, security, scalability, resilience, and cost optimization.
• Experience implementing observability solutions covering monitoring, logging, tracing, alerting, and operational dashboards.
• Understanding of metadata management, data lineage, data governance, and semantic-layer concepts is highly valuable.

Good to Have

• Experience supporting enterprise GenAI platforms, AI governance, model management, and AI operationalization.
• Experience with GitOps, DevSecOps, Platform Engineering, and Reliability Engineering practices.
• Exposure to data governance, data quality, metadata management, and model lifecycle automation.
• Experience creating reusable internal developer platforms and self-service engineering tools at enterprise scale.
• Banking, AML, fraud detection, financial crime, or risk analytics domain experience is an advantage.

We are looking for an experienced DevOps Engineer to take ownership of production infrastructure, cloud environments, Kubernetes platforms, and infrastructure automation. This is a hands-on role for someone who enjoys solving complex infrastructure challenges and is comfortable being responsible for systems in production.

Key Responsibilities

• Own and operate production infrastructure, including participating in an on-call rotation and responding to production incidents.
• Design, operate, and continuously improve Kubernetes clusters in production.
• Manage and automate infrastructure using Infrastructure as Code, primarily with Terraform.
• Build, maintain, and optimise cloud infrastructure across AWS, GCP, or Azure.
• Work extensively with Linux, including system administration, networking, troubleshooting, and system-level configuration.
• Manage production deployment and GitOps workflows using ArgoCD.
• Improve infrastructure reliability, scalability, security, monitoring, and operational efficiency.
• Troubleshoot complex production issues and drive problems through to resolution.
• Develop automation and processes that reduce manual operational work.
• 
  

Essential Requirements

• 4+ years of hands-on experience operating production infrastructure, with personal ownership and responsibility for live systems, including on-call experience.
• Deep, hands-on Kubernetes experience — you must have operated and managed Kubernetes clusters, rather than simply deploying applications onto clusters managed by another team.
• Strong experience with Infrastructure as Code, with Terraform strongly preferred. Experience with Pulumi or CloudFormation is also considered.
• Strong experience with at least one major cloud platform, ideally AWS. Strong GCP or Azure experience is also welcome, provided you are willing to work with AWS.
• Strong Linux skills and confidence working from the command line, including networking, troubleshooting, system configuration, and performance issues.
• Production experience with ArgoCD and GitOps-based deployment workflows.
• Strong troubleshooting and problem-solving skills, with the ability to take ownership of production incidents and infrastructure issues.

Nice to Have

Experience with email infrastructure would be a strong advantage, particularly:

• Exim
• IMAP / SMTP
• Postfix
• Dovecot
• General mail server administration and maintenance

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.

 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

Build production-grade cloud infrastructure that powers enterprise applications with cutting-edge DevOps practices.

What you'll do:

• Design CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI)
• Containerize apps with Docker, deploy on Kubernetes clusters
• Manage infrastructure as code (Terraform, CloudFormation)
• Set up monitoring (Prometheus, Grafana, ELK Stack)
• Cloud migrations (AWS EC2, EKS, RDS → GCP equivalent)
• Optimize costs and performance for live production systems

What we need:

• Basic Python/Bash scripting
• Docker basics, Git workflows
• Cloud exposure (AWS/GCP/Azure free tier projects)
• Problem-solving mindset, eagerness to learn

Real impact:

• Deploy apps used by 1000+ daily users
• Work with senior DevOps engineers on client deliverables
• Build portfolio for FAANG-level interviews

 Job Description:

• Job title : Senior DevOps Engineer (On-Premises Automation)        
• Experience: 8+ years
• Location: Chennai / Pune / Hyderabad / Bangalore
• Shift: UK Shift
• Work Mode: Onsite (WFO)

Roles and Responsibilities:

• This engagement automates end-to-end infrastructure build provisioning across on-prem and Azure. The team will build a shared ServiceNow-led intake, approval, orchestration, and closed-loop status model, using Jenkins/Ansible for on-prem builds and Azure DevOps/Terraform for cloud builds. Automation includes standards, security/compliance controls, scan gates, CMDB/change updates, and handover.              

Key Responsibilities:

• Lead secure and repeatable on-prem build provisioning pipelines
• Lead Jenkins CI/CD for automated on-prem provisioning and configuration.
• Create pipeline templates for VM/physical host, OS deployment, configuration, certification, and rollback.
• Embed hardened-image validation, scan gates, secrets handling, approvals, and audit evidence.
• Lead Ansible roles, PowerShell modules, test automation, and code reviews.
• Implement logging, monitoring, and root-cause analysis; support UAT and hypercare.       

Required Qualifications:

• 8–10 years in DevOps, platform engineering, or infrastructure automation.
• Bachelor’s degree or equivalent experience.
• Jenkins
• Git, CI/CD
• Ansible, PowerShell
• Python, IaC
• security scanning, secrets management
• Windows/Linux.