Senior SRE / DevOps / Infrastructure Engineer – AI Agentic Systems

We are looking for an SRE with DevOps expertise to maintain production system reliability, availability, and performance through automation, monitoring, and efficient incident management.

Responsibilities

• Monitor production systems and troubleshoot incidents.
• Manage Linux/Unix servers and cloud infrastructure.
• Develop and maintain CI/CD pipelines.
• Automate operational tasks using scripting.
• Manage infrastructure using Terraform or Ansible.
• Work with Docker and Kubernetes.
• Perform root cause analysis (RCA) and improve system reliability.

Required Skills

• SRE and DevOps experience.
• Linux/Unix administration.
• AWS, Azure, or GCP.
• CI/CD tools: Jenkins, GitLab, or GitHub Actions.
• Docker and Kubernetes.
• Terraform and Ansible.
• Python, Shell, or Bash scripting.
• Monitoring tools: Prometheus, Grafana, Splunk, or Datadog.
• Incident management and troubleshooting.

Senior Cloud Site Reliability Engineer (CSRE) – Azure

About Searce:

Searce is an AI-native, engineering-led modern technology consultancy that empowers

clients to futurify their businesses by delivering real, intelligent business outcomes. As a

trusted partner for over 3,000 clients globally, Searce specializes in cloud modernization,

data engineering, applied AI, and robust cloud platform security. Driven by a "HAPPIER"

cultural mindset and our proprietary evlos problem-solving framework, we eliminate

bureaucratic fluff to build working prototypes fast and scale enterprise production

environments intelligently. We don't just fix systems; we leverage multi-cloud technologies

to transform client operations into distinct competitive advantages.

Position Overview:

We are looking for a high-caliber Senior or Lead Cloud Site Reliability Engineer (CSRE) to

architect, secure, and stabilize next-generation hybrid and multi-cloud environments.

Operating at the intersection of infrastructure design, security compliance, and production

operations, you will serve as the technical Subject Matter Expert (SME) across GCP, Azure,

and AWS.

Whether optimizing a microservice mesh on GKE, tuning autoscaling on AKS, or driving a

massive disaster recovery drill across AWS regions, your focus will be absolute reliability. For

the Lead path, you will couple this deep engineering toolkit with stakeholder management

and mentorship to drive an elite operational culture.

Experience & Level Expectation:

Years of Experience: 3 to 10 years of intensive, hands-on production operations

experience in a dedicated DevOps, Cloud Platform Engineering, or SRE role.

Associate level (3-5 Years): Expected to show flawless execution of IaC, advanced

triaging of infrastructure failures, and ownership of the CI/CD and deployment

lifecycles.

Intermediate level (5-10 Years): Expected to take architectural ownership, serve as

primary Incident Commander for complex outages, design cross-cloud governance

frameworks, and act as a reliable bridge between technical teams and client

leadership.

Key Responsibilities & Role Expectations:

Multi-Cloud Platforms & Orchestration: Design, configure, and maintain

production-grade Kubernetes clusters across major platforms (AKS).

Manage advanced network routing, service meshes (e.g., Istio), and multi-tenant

isolation.

Infrastructure as Code (IaC) & GitOps: Build declarative, enterprise-grade, reusable

infrastructure components using Terraform or Crossplane. Standardize automated

environment provisioning to eliminate configuration drift across multi-branch

environments.

Incident Management & Reliability (SRE): Own and optimize the production on-call

rotation. Lead rapid mitigation strategies for Sev-1/Sev-2 system outages, reducing

Mean Time to Recovery (MTTR) through centralized log and metric correlation.

Root Cause Analysis (RCA): Facilitate rigorous, blameless post-incident reviews to

identify core architectural vulnerabilities and establish long-term fixes preventing

recurrence.

Lifecycle, Patching & Upgrades: Plan and execute zero-downtime cluster upgrades,

operating system patching strategies (Linux/Windows), database lifecycle updates,

and multi-region Disaster Recovery (DR) failover drills.

Core Core Operations & Legacy Integration: Manage enterprise-level hybrid

networking architecture (VPCs, Firewalls, Load Balancers, DNS routing, and DHCP

configurations) while effectively connecting cloud native services to legacy

infrastructures like Active Directory.

Security & Governance: Embed Zero Trust policies, secure secrets management

(Secrets Manager/Key Vault), and continuous vulnerability patching into the

automated SDLC pipeline.

Required Technical Skills:

- Microsoft Azure: Azure Virtual Machines, Virtual Networks, Azure Active Directory, Azure Update Management.

- Containers & Orchestration

• Production-level management of GKE, AKS, and EKS.
• Advanced mastery of Docker, Helm, Kubernetes StatefulSets, Pod Disruption

Required Skills:

• Strong experience in Site Reliability Engineering (SRE) and DevOps practices.
• Hands-on experience with CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI/CD.
• Strong knowledge of AWS, Azure, or GCP cloud platforms.
• Experience with Docker, Kubernetes, and container orchestration.
• Hands-on experience with Terraform, Ansible, or other Infrastructure as Code (IaC) tools.
• Experience with monitoring and observability tools such as Prometheus, Grafana, Splunk, ELK, or Datadog.
• Good scripting skills in Python, Bash, or Shell scripting.
• Understanding of SLI, SLO, SLA, error budgets, and service reliability.
• Experience in incident management, troubleshooting, root-cause analysis (RCA), and production support.
• Knowledge of system performance monitoring, capacity planning, high availability, and disaster recovery.
• Experience with Linux/Unix administration and networking fundamentals.
• Familiarity with Agile methodologies, Git, and automated deployment practices.

Job Summary

We are looking for an experienced SRE DevOps Engineer to manage production infrastructure, improve system reliability, automate operational tasks, and support scalable cloud environments. The candidate should have strong experience in Site Reliability Engineering (SRE), DevOps tools, monitoring, incident management, and automation.

Key Responsibilities

• Monitor application and infrastructure performance to ensure high availability and reliability.
• Manage production incidents, troubleshooting, root cause analysis, and resolution.
• Implement and maintain CI/CD pipelines for automated deployments.
• Manage cloud infrastructure on AWS, Azure, or GCP.
• Automate repetitive operational tasks using Python, Shell, or Bash scripting.
• Work with Docker, Kubernetes, and container orchestration technologies.
• Implement monitoring and alerting using tools such as Prometheus, Grafana, Splunk, or Datadog.
• Manage infrastructure as code using Terraform or Ansible.
• Define and monitor SLIs, SLOs, and SLAs.
• Collaborate with development, infrastructure, and support teams to improve system reliability.
• Participate in on-call support and disaster recovery activities.

Mandatory Skills

• Site Reliability Engineering (SRE)
• DevOps and Production Support
• Linux/Unix Administration
• Cloud Platforms: AWS, Azure, or GCP
• CI/CD Tools: Jenkins, GitLab CI, or GitHub Actions
• Scripting: Python, Shell, or Bash
• Docker and Kubernetes
• Monitoring and Observability: Splunk, Grafana, Prometheus, or Datadog
• Incident Management and Root Cause Analysis

Job Summary

We are looking for an experienced SRE / DevOps Engineer with strong expertise in production support, site reliability engineering, cloud infrastructure, automation, and monitoring. The candidate should have experience maintaining highly available systems, troubleshooting production issues, and improving infrastructure reliability and performance.

Mandatory Skills

• Site Reliability Engineering (SRE)
• DevOps Engineering
• Production Support
• Linux Administration
• Cloud Infrastructure (AWS / Azure / GCP)
• Kubernetes and Docker
• CI/CD pipelines
• Monitoring and Observability
• Scripting using Python / Shell
• Incident Management and Root Cause Analysis

Key Responsibilities

• Monitor and maintain the availability, reliability, and performance of applications and infrastructure.
• Handle production incidents, troubleshoot issues, and perform root cause analysis.
• Manage and automate infrastructure deployment and operational tasks.
• Work with CI/CD pipelines and container orchestration platforms.
• Implement monitoring, alerting, and observability solutions.
• Collaborate with development and operations teams to improve system reliability.
• Support cloud infrastructure, Linux environments, and production deployments.
• Identify recurring issues and implement preventive measures to reduce downtime.

Role Overview

We are looking for a DevOps / Platform Engineer with 3–4 years of experience to help manage AWS cloud infrastructure, automation, and AI-ready platform operations. You will work closely with engineering and AI teams to ensure scalable, secure, and reliable deployments.

Key Responsibilities

1. AWS & Infrastructure: Manage core AWS services (EC2, EKS, Lambda, RDS, S3, VPC) using Infrastructure-as-Code (Terraform, CloudFormation, or CDK).
2. AI/ML Workflows: Support infra for AI applications, model serving, vector databases, and GPU-based workloads.
3. CI/CD & Automation: Build and maintain deployment pipelines using GitHub Actions, GitLab CI, or Jenkins.
4. Containers & Kubernetes: Deploy and maintain containerized applications using Docker and Kubernetes (EKS) or ECS.
5. Observability & Incident Support: Maintain dashboards and alerts with CloudWatch, Prometheus, or Grafana, and participate in on-call response.
6. Security & FinOps: Apply AWS security best practices (IAM, encryption, secrets) and assist with cloud cost optimization.

Must-Have Skills & Qualifications

1. 3–4 years of experience in DevOps, SRE, or Cloud Infrastructure Engineering.
2. AWS & Containers: Good working knowledge of core AWS services, Docker, and Kubernetes (EKS).
3. Infrastructure-as-Code: Practical experience with Terraform, CloudFormation, or AWS CDK.
4. Linux & Networking: Solid fundamentals in Linux systems, DNS, routing, and load balancing.
5. Scripting: Hands-on scripting proficiency in Python, Bash, or Go.
6. CI/CD & Observability: Experience building CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins) and using monitoring tools (CloudWatch, Prometheus, Grafana, or Datadog).

Nice-to-Have Skills

1. Basic exposure to AI/ML infrastructure, model serving, or GPU-based compute.
2. Experience with event-driven messaging systems (Kafka, Redis, or SQS).
3. Familiarity with GitOps tools and Helm (ArgoCD, Flux, or OpenTelemetry).
4. AWS Certifications (Solutions Architect Associate, SysOps Administrator, or DevOps Engineer).

We are looking for an experienced SRE / DevOps Engineer with strong expertise in production support, site reliability engineering, cloud infrastructure, automation, and monitoring. The candidate should have experience maintaining highly available systems, troubleshooting production issues, and improving infrastructure reliability and performance.

Mandatory Skills

• Site Reliability Engineering (SRE)
• DevOps Engineering
• Production Support
• Linux Administration
• Cloud Infrastructure (AWS / Azure / GCP)
• Kubernetes and Docker
• CI/CD pipelines
• Monitoring and Observability
• Scripting using Python / Shell
• Incident Management and Root Cause Analysis

 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

Job Description

Role: Site Reliability Engineer (SRE)

Experience: 8+ Years

Location: Bangalore

Notice Period: Immediate Joiners Only

Key Responsibilities

• Implement reliability practices across applications and cloud platforms.
• Monitor and troubleshoot production systems using observability tools.
• Manage incidents, perform root cause analysis (RCA), and prepare post-incident reports.
• Develop and maintain CI/CD pipelines and automate operational tasks.
• Improve system availability, performance, scalability, and operational stability.
• Develop proof-of-concepts and convert them into production-ready solutions.
• Collaborate with engineering teams to improve reliability and reduce operational toil.
• Use AI tools responsibly to enhance operational efficiency and productivity.

Required Skills

• Strong SRE fundamentals and production support experience.
• Hands-on experience with AWS cloud services and best practices.
• Observability tools: Splunk, Grafana, and Datadog.
• Understanding of metrics, logs/events, and distributed tracing.
• Familiarity with Amazon Connect and contact center technologies, including voice, call recording, and telephony.
• CI/CD tools: Jenkins/Jules; source control: Git/Bitbucket.
• Scripting and automation skills are preferred.
• Experience in incident management, troubleshooting, and RCA documentation.
• Cloud certification or experience supporting cloud-based applications.
• Familiarity with AI concepts and responsible AI tool usage.

We're seeking an experienced Engineer to join our engineering team, handling massive-scale data processing and analytics infrastructure that supports over 1B daily events, 3M+ DAU, and 50k+ hours of content. The ideal candidate will bridge the gap between raw data collection and actionable insights, while supporting our ML initiatives.

Key Responsibilities

• Lead and scale the Infrastructure Pod, setting technical direction for data, platform, and DevOps initiatives.
• Architect and evolve our cloud infrastructure to support 1B+ daily events — ensuring reliability, scalability, and cost efficiency.
• Collaborate with Data Engineering and ML pods to build high-performance pipelines and real-time analytics systems.
• Define and implement SLOs, observability standards, and best practices for uptime, latency, and data reliability.
• Mentor and grow engineers, fostering a culture of technical excellence, ownership, and continuous learning.
• Partner with leadership on long-term architecture and scaling strategy — from infrastructure cost optimization to multi-region availability.
• Lead initiatives on infrastructure automation, deployment pipelines, and platform abstractions to improve developer velocity.
• Own security, compliance, and governance across infrastructure and data systems.

Who You Are

• Previously a Tech Co-founder / Founding Engineer / First Infra Hire who scaled a product from early MVP to significant user or data scale.
• 5–12 years of total experience, with at least 2+ years in leadership or team-building roles.
• Deep experience with cloud infrastructure (AWS/GCP), 
• Experience with containers (Docker, Kubernetes), and IaC tools (Terraform, Pulumi, or CDK).
• Hands-on expertise in data-intensive systems, streaming (Kafka, RabbitMQ, Spark Streaming), and distributed architecture design.
• Proven experience building scalable CI/CD pipelines, observability stacks (Prometheus, Grafana, ELK), and infrastructure for data and ML workloads.
• Comfortable being hands-on when needed — reviewing design docs, debugging issues, or optimizing infrastructure.
• Strong system design and problem-solving skills; understands trade-offs between speed, cost, and scalability.
• Passionate about building teams, not just systems — can recruit, mentor, and inspire engineers.

Preferred Skills

• Experience managing infra-heavy or data-focused teams.
• Familiarity with real-time streaming architectures.
• Exposure to ML infrastructure, data governance, or feature stores.
• Prior experience in the OTT / streaming / consumer platform domain is a plus.
• Contributions to open-source infra/data tools or strong engineering community presence.

What We Offer

• Opportunity to build and scale infrastructure from the ground up, with full ownership and autonomy.
• High-impact leadership role shaping our data and platform backbone.
• Competitive compensation + ESOPs.
• Continuous learning budget and certification support.
• A team that values velocity, clarity, and craftsmanship.

Success Metrics

• Reduction in infra cost per active user and event processed.
• Increase in developer velocity (faster pipeline deployments, reduced MTTR).
• High system availability and data reliability SLAs met.
• Successful rollout of infra automation and observability frameworks.
• Team growth, retention, and technical quality.