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Striim (pronounced “stream” with two i’s for integration and intelligence) was founded in 2012 with a simple goal of helping companies make data useful the instant it’s born.

Striim’s enterprise-grade, streaming integration with intelligence platform makes it easy to build continuous, streaming data pipelines – including change data capture (CDC) – to power real-time cloud integration, log correlation, edge processing, and streaming analytics

2 - 5 Years of Experience in any Programming any language (Polyglot Preferred ) & System Operations • Awareness of Devops & Agile Methodologies • Proficient in leveraging CI and CD tools to automate testing and deployment . • Experience in working in an agile and fast paced environment . • Hands on knowledge of at least one cloud platform (AWS / GCP / Azure). • Cloud networking knowledge: should understand VPC, NATs, and routers. • Contributions to open source is a plus. • Good written communication skills are a must. Contributions to technical blogs / whitepapers will be an added advantage.

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.

Primary Skills: 

Observability - ELK (Elactic/Kibana), Prometheus, Grafana, PromQL

Software and automation - Java, Python/Shell/Bash, Rest-SOAP API, docker containerization, Kubernetes, Kafka

Reliability and DR engineering - Distributed architecture and distributed system fundamentals, micro services, and event-driven architecture.

Cross-team coordination, incident triage and resolution, leadership and stakeholder management.

Secondary Skills:

Lang-chain, Langraph, RAG, MCP

Experience with working on LLM's and integrating with the existing applications

Python - FastAPI

Cache - Redis

Program Details:

Design, build, and ship LLM-powered and agentic product features that enhance the team efforts and outcomes.

Build agentic AI systems that reason over context, invoke tools, take real actions, and recover gracefully from failure.

Work on integrating the existing AI tools and should know major AI frameworks and libraries. 

Own service reliability and operational governance by defining SLA's, managing error budgets, and reporting reliability (MTTD, MTTR) to leadership for prioritization, risk decisions and planning.

Architect and continuously optimize the observability of platform using Kibana/Elastic (ELF) along with other observability tools like Prometheus, Grafana (dashboards, metrics, alert lifecycle), improving detection quality, reducing noise/toil, and enabling faster triage and measurable uptime improvements.

Engineer advance alerting and automation capabilities with Kibana alerting and anomaly detections and integrating response workflows (routing, runbooks, remediation scripts) to standardize on-call execution and accelerate restoration of services.

Lead incident response for customer-impacting issues across teams-coordination, communications, service restoration, and blameless RCA-then corrective actions that prevent recurrence and reduce operational risk.

Design, automate and validate Disaster Recovery and failover for critical services/journeys (RTO/RPO alignment, DR Drills), ensuring resiliency under failure scenarios and improving recovery.

Consult and partner with application teams by providing production readiness inputs (Resiliency patterns, availability, performance/capacity considerations) and driving platform enhancements that improve stability while optimizing infrastructure and observability spend.

If you are interested for this role, kindly acknowledge this email with your interest.

Why this role exists

Our infrastructure footprint is growing faster than our headcount, and we believe most of that

gap should be closed by automation and AI agents — not by hiring more humans to do toil. We

need someone early in their career who treats manual work as a bug, ships scripts and agents

instead of tickets, and wants to grow into deeper ownership over the next two years.

You will not be the most senior person on the team. You will be the one who multiplies the team.

What you'll own

In your first 1 months

• Take ownership of one slice of our CI/CD pipeline and make it measurably

faster, more reliable, or cheaper. We expect a number on a dashboard to move.

• Build at least three internal automations that replace manual ops toil —

using AI agents (Claude Code, agentic CLIs, scripted LLM workflows) as your force

multiplier.

• Be the first responder for a defined set of alerts. Write the runbooks. Drive

the alert volume down.

• Support senior engineers on AI/ML infrastructure (GPU nodes, inference

services, model deployment) — observe, document, and gradually take on contained

changes under review.

By 3 months you should be

• The go-to person for at least two production systems.

• Shipping routine infrastructure changes without needing senior review.

• Treating "manual" as a code smell.

Required (we will reject without these)

• 0–3 years hands-on experience with one major cloud (AWS, GCP, or

Azure — one is fine, depth beats breadth).

• Fluent in Linux command line, bash, and at least one scripting language

(Python or Go preferred).

• Have shipped something to production that real users hit. A side project

counts; a graded coursework lab does not.

• Comfortable with Docker — you can explain what an image vs. a

container is and why it matters.

• Working knowledge of networking fundamentals: DNS, HTTP/HTTPS,

TLS, ports, basic subnets — enough to debug "it works on my machine."

• Git fluency: branches, merges, rebases, conflict resolution.

• CI/CD pipelines — you have authored or substantially modified pipelines

in GitHub Actions, GitLab CI, ArgoCD, Jenkins, or similar. Not just "I clicked Re-run."

• Kubernetes basics — kubectl for real work, can read pod logs,

understand deployments and services, can debug a CrashLoopBackOff without

panicking. You do not need to have run a cluster; you do need to have lived inside one.

• Active user of AI coding agents (Claude Code, Cursor, Copilot, agentic

CLIs, etc.). You should be able to walk us through specific tasks where they made you

faster, and specific tasks where they failed you and how you noticed. "I have tried it" is

not enough.

Bonus (real plus, not required)

• Infrastructure as Code: Terraform, Pulumi, or Ansible.

• Observability: Prometheus/Grafana, Datadog, OpenTelemetry, any APM.

• Have built or extended an LLM-based agent — a custom MCP server, a

scripted multi-step workflow, an internal tool that calls models in a loop. Anything beyond

chat-with-Claude.

• Exposure to GPU workloads, model serving (vLLM, Triton, TGI, etc.), or

ML pipelines.

What we don't care about

• Whether your degree is in CS — or whether you have a degree at all.

• Brand-name companies on your resume.

• Certifications. They are fine. They do not substitute for having shipped.

How we work

• We default to automation. If you do something manually twice, the third

time you script it or hand it to an agent.

• AI agents are part of the workflow, not a novelty. Expect interview

questions about exactly how you use them — and where you have caught them being

wrong.

• Small, reversible changes beat big-bang rollouts.

• Postmortems are blameless and written down.

• We push back on each other. If you only execute, you will be unhappy

here.

How to apply

Send:

• Your resume.

• A short note (≤200 words) describing one infra or automation problem you

solved, and how AI agents factored in — or did not, and why. We read these. Generic

notes get rejected.

Internal note — delete before posting externally

• Comp band, location policy, team name, and reporting line marked

[CONFIRM] need to be filled in before this goes external.

• The Required list is intentionally tight: CI/CD and Kubernetes basics

promoted from bonus. Expect this to filter ~80% of typical junior DevOps applicants. The

remaining pool will skew toward people who have actually shipped infra at a startup, not

bootcamp grads or pure cloud-cert holders.

• IaC, observability, agent-building, and GPU/ML serving stay as bonus.

Promoting any of these to required at 0–3 yrs collapses the pool to near-zero or forces

hiring senior people at junior comp. If you want IaC required, re-level this to mid (3–5

yrs) and raise the band.

• Screening implication: the resume screen should explicitly check for

CI/CD pipeline authorship and any K8s-touching production work. If neither is on the

resume, reject at screen. Do not waste interview slots.

• Pipeline watch: if fewer than ~15 qualified resumes after 2 weeks of

active sourcing, the first thing to relax is the AI-agent-fluency bar (move to bonus and

screen for it in interview instead). Do not relax the "shipped to production" requirement

— that is the load-bearing filter.

We are looking for a highly skilled DevOps/Cloud Engineer with over 6 years of experience in infrastructure automation, cloud platforms, networking, and security. If you are passionate about designing scalable systems and love solving complex cloud and DevOps challenges—this opportunity is for you.

Key Responsibilities

• Design, deploy, and manage cloud-native infrastructure using Kubernetes (K8s), Helm, Terraform, and Ansible
• Automate provisioning and orchestration workflows for cloud and hybrid environments
• Manage and optimize deployments on AWS, Azure, and GCP for high availability and cost efficiency
• Troubleshoot and implement advanced network architectures including VPNs, firewalls, load balancers, and routing protocols
• Implement and enforce security best practices: IAM, encryption, compliance, and vulnerability management
• Collaborate with development and operations teams to improve CI/CD workflows and system observability

Required Skills & Qualifications

• 6+ years of experience in DevOps, Infrastructure as Code (IaC), and cloud-native systems
• Expertise in Helm, Terraform, and Kubernetes
• Strong hands-on experience with AWS and Azure
• Solid understanding of networking, firewall configurations, and security protocols
• Experience with CI/CD tools like Jenkins, GitHub Actions, or similar
• Strong problem-solving skills and a performance-first mindset

Why Join Us?

• Work on cutting-edge cloud infrastructure across diverse industries
• Be part of a collaborative, forward-thinking team
• Flexible hybrid work model – work from anywhere while staying connected
• Opportunity to take ownership and lead critical DevOps initiatives

• Bachelor of Computer Science or Equivalent Education
• At least 5 years of experience in a relevant technical position.
• Azure and/or AWS experience
• Strong in CI/CD concepts and technologies like GitOps (Argo CD)
• Hands-on experience with DevOps Tools (Jenkins, GitHub, SonarQube, Checkmarx)
• Experience with Helm Charts for package management
• Strong in Kubernetes, OpenShift, and Container Network Interface (CNI)
• Experience with programming and scripting languages (Spring Boot, NodeJS, Python)
• Strong container image management experience using Docker and distroless concepts
• Familiarity with Shared Libraries for code reuse and modularity
• Excellent communication skills (verbal, written, and presentation)

Note: Looking for immediate joiners only.

The candidates should have:

·  Strong knowledge on Windows and Linux OS

·   Experience working in Version Control Systems like git

·  Hands-on experience in tools Docker, SonarQube, Ansible, Kubernetes, ELK.

·  Basic understanding of SQL commands

·  Experience working on Azure Cloud DevOps

DevOps Engineer

Job Description:

The position requires a broad set of technical and interpersonal skills that includes deployment technologies, monitoring and scripting from networking to infrastructure. Well versed in troubleshooting Prod issues and should be able to drive till the RCA.

Skills:

• Manage VMs across multiple datacenters and AWS to support dev/test and production workloads.
• Strong hands-on over Ansible is preferred
• Strong knowledge and hands-on experience in Kubernetes Architecture and administration.
• Should have core knowledge in Linux and System operations.
• Proactively and reactively resolve incidents as escalated from monitoring solutions and end users.
• Conduct and automate audits for network and systems infrastructure.
• Do software deployments, per documented processes, with no impact to customers.
• Follow existing devops processes while having flexibility to create and tweak processes to gain efficiency.
• Troubleshoot connectivity problems across network, systems or applications.
• Follow security guidelines, both policy and technical to protect our customers.
• Ability to automate recurring tasks to increase velocity and quality.
• Should have worked on any one of the Database (Postgres/Mongo/Cockroach/Cassandra)
• Should have knowledge and hands-on experience in managing ELK clusters.
• Scripting Knowledge in Shell/Python is added advantage.
• Hands-on Experience over K8s based Microservice Architecture is added advantage.

• Experience working on Linux based infrastructure
• Strong hands-on knowledge of setting up production, staging, and dev environments on AWS/GCP/Azure
• Strong hands-on knowledge of technologies like Terraform, Docker, Kubernetes
• Strong understanding of continuous testing environments such as Travis-CI, CircleCI, Jenkins, etc.
• Configuration and managing databases such as MySQL, Mongo
• Excellent troubleshooting
• Working knowledge of various tools, open-source technologies, and cloud services
• Awareness of critical concepts in DevOps and Agile principles