Platform Engineering Lead

What You Will Own 

Platform Architecture 

• Full architectural ownership of the non-AWS toolchain: CI/CD, observability, event streaming, automation, secrets, and deployment infrastructure 
• Define, build, and enforce platform standards across portfolio products 
• Terraform IaC for all infrastructure — nothing provisioned manually, everything versioned and reviewed 
• Self-service developer platform so product teams ship without waiting on platform 

Event Streaming & Pipeline Infrastructure 

• Own the event streaming architecture, operational standards, and health monitoring across all products using real-time pipelines 
• Design and maintain batch processing infrastructure alongside live event flows 
• Ensure pipeline reliability, throughput, and cost are actively managed at scale 

CI/CD & Deployment 

• Build and maintain CI/CD pipelines (GitHub Actions) across all portfolio products 
• Automate triage and retry logic for known failure classes — flaky tests, dependency timeouts, OOM kills — so engineers are only paged for genuinely novel failures 
• Deployment standards: release management, rollback mechanisms, canary and blue-green patterns where justified 

Observability & Reliability 

• Own the full observability stack: Grafana, Prometheus, and Loki across all products 
• SLOs and error budgets defined per product; reliability tracked consistently 
• Build alerting that correlates signals and surfaces diagnostic context alongside notifications — so on-call engineers arrive at an incident with hypotheses, not a blank screen 
• Incident response: on-call design, escalation playbooks, post-mortem facilitation 
• Automated remediation scoped to a defined set of safe, idempotent actions — container restarts, ECS task scaling, known rollback patterns. Novel or ambiguous failures escalate to a human with full context attached 

Acquisition Onboarding 

• Platform audit and gap analysis for every new acquisition — assessing CI/CD maturity, IaC coverage, observability gaps, and security posture 
• Migration plan and execution for each portfolio company joining the platform.
• Target: full platform integration within a defined window per acquisition 

What We're Looking For 

Experience & Background 

• 8–12 years in platform engineering, DevOps, or SRE — with clear evidence of increasing ownership over time 
• Strong Terraform depth across multi-environment, multi-account setups 
• CI/CD ownership across a multi-product environment with GitHub Actions 
• Experience with event streaming infrastructure at production scale — design, operations, reliability, and cost management 
• Hands-on Grafana, Prometheus, and Loki in production 
• AWS operational depth: ECS, EKS, RDS, IAM, VPC, CloudWatch, Cost Explorer 
• SRE fundamentals: SLOs, error budgets, on-call design, post-mortem culture 
• Acquisition or greenfield platform integration experience strongly preferred 

Required Skills & Qualifications

• Experience: 10+ years in Cloud Engineering, Infrastructure, or DevOps, with strong hands-on GCP experience.
• GCP Expertise: GKE, Compute Engine, IAM, VPC, Cloud Storage, Cloud SQL, Cloud Run, Cloud Functions, and Load Balancing.
• Kubernetes & Containers: GKE, Docker, Kubernetes networking, Helm, and troubleshooting.
• DevOps & IaC: Azure DevOps, Terraform, CI/CD pipelines, and infrastructure automation.
• Scripting: Python, Bash, or PowerShell.
• Security & Operations: Cloud security, IAM, monitoring, incident management, and cost optimization.
• Leadership & Ownership: Proven experience in team leadership, cross-functional collaboration, stakeholder management, managing multiple product-line deliverables, and handling competing priorities and ad hoc requests.
• Additional Advantage: Experience with Microsoft Azure.

Job Title : SDE 3 – Infrastructure Platform Engineer

Experience : 5.5 to 8.5 Years

Number of Positions : 2

Employment Type : C2H (Contract to Hire)

Work Mode : Remote during contractual period → 5 Days WFO after conversion

Contract Duration : 3 Months

Post-Conversion Location : Pune

Notice Period : Immediate Joiners / Serving Notice Period / Up to 15 Days preferred

(Candidates officially serving a 30-day notice period may also be considered if they are on the bench and have a negotiable joining date)

Role Overview :

We are looking for an experienced SDE 3 – Infrastructure Platform Engineer to design, build, and operate scalable, secure, and highly reliable cloud infrastructure and internal platform capabilities.

The ideal candidate will have strong hands-on experience in Cloud Infrastructure, Infrastructure as Code (IaC), CI/CD, Docker, Kubernetes, automation, observability, networking, and distributed systems.

Mandatory Skills : AWS / Azure / GCP, Terraform / CloudFormation, Kubernetes, Docker, CI/CD, Platform / Infrastructure Engineering, Python / Go / Java / Ruby, Networking, Cloud Security, Distributed Systems, Scalability & Reliability, Strong Coding & Automation.

Key Responsibilities :

• Design and maintain scalable, highly available infrastructure on AWS / GCP / Azure.
• Build and manage Infrastructure as Code (IaC) using Terraform, CloudFormation, or similar tools.
• Develop automation for infrastructure provisioning, deployments, monitoring, and operations.
• Manage and optimize Docker and Kubernetes workloads.
• Build internal platform tools to improve developer productivity and engineering efficiency.
• Implement monitoring, logging, alerting, and observability solutions.
• Participate in incident response, RCA, postmortems, and reliability improvements.
• Design and improve CI/CD pipelines and deployment automation.
• Contribute to system design, architecture discussions, scalability, security, and cost optimization.
• Collaborate with application, data, and product engineering teams.

Required Skills :

• 5.5 to 8.5 years of experience in Infrastructure / Platform Engineering or similar roles.
• Strong hands-on experience with AWS, GCP, or Azure.
• Strong expertise in Terraform / CloudFormation.
• Experience with CI/CD, Docker, and Kubernetes.
• Strong programming skills in at least one of:
• Python, Go, Java, or Ruby.
• Good understanding of networking, cloud security, distributed systems, scalability, and reliability.
• Experience working with production infrastructure and highly available systems.
• Strong troubleshooting and problem-solving skills.

Nice to Have :

• Experience with SRE practices and production on-call ownership.
• Experience in fintech, payments, banking, or transaction-heavy systems.
• Knowledge of cloud security, compliance, or FinOps/cost optimization.
• Experience building internal developer platforms or productivity tools.
• Previous product company experience.

Interview Process :

Round 1 : Take-Home Coding Assignment – Submit within 48 hours

Round 2 : Coding Assignment Discussion – 1 Hour

Round 3 : Technical Managerial Round – 30 Minutes

Note : The take-home coding assignment is mandatory. Candidates should be comfortable completing and submitting the assignment within 48 hours before proceeding.

Ideal Candidate :

Strong Platform / Infrastructure Engineer with hands-on experience in :

Cloud + Terraform / CloudFormation + Kubernetes + CI/CD + Programming + SRE / Production Operations

Pure DevOps profiles without strong coding and platform engineering experience are not preferred.

About the Team

SecurITe’s mission is to build an Agentic-AI driven security platform that protects critical infrastructure from modern cyber threats. Our focus is on delivering highly performant, resilient, and intelligent network security systems that help defenders stay ahead of adversaries.

About the Role

We’re looking for an exceptional Platform Engineer to help lead the development of our next-generation cybersecurity AI platform. This is a rare opportunity to shape how agentic AI transforms the future of cyber defense.

As a Platform Engineer, you will design, build, and operate the foundational infrastructure, deployment systems, and developer platforms that power our cybersecurity products across cloud and on-premise environments. You will work at the intersection of infrastructure engineering, cloud-native technologies, automation, reliability, and security to enable scalable and resilient product delivery.

You’ll collaborate closely with AI/ML, backend, security, QA, and product engineering teams to create self-service platforms, deployment pipelines, observability systems, and operational tooling that accelerate innovation while maintaining enterprise-grade reliability and security.

This role is ideal for Linux platform engineers and system specialists who excel at solving complex system challenges, automating wherever possible, and building resilient platforms that enable teams to move faster with confidence.

Why This Role Matters

Cybersecurity is undergoing a fundamental shift. AI is no longer an enhancement—it’s becoming the core engine of how detection, investigation, and response are executed. As our Platform Engineer, you will architect and build the infrastructure, automation, deployment, and operational systems that make this transformation real.

Your work will directly influence the scalability, reliability, and security of our AI-driven cybersecurity platform across both cloud and enterprise on-premise deployments. You’ll help establish the operational backbone that enables rapid innovation, secure product delivery, and resilient large-scale deployments in mission-critical environments.

This is a chance to solve novel technical challenges involving distributed systems, hybrid infrastructure, observability, automation, and secure software delivery while shaping how defenders outpace modern attackers.

What You’ll Do

●    Design, build, and own AWS infrastructure from the ground up (VPC architecture, EC2 fleet management, IAM, networking, security groups)

●    Administer and harden AlmaLinux VMs across production, staging, and dev environments

●    Build automation for provisioning, patching, and configuration management (infrastructure-as-code, config management tooling)

●    Design and implement observability: monitoring, logging, alerting, and on-call-worthy SLAs from scratch

●    Lead incident response — diagnosis, RCA, and post-incident documentation — with no dedicated ops team to escalate to

●    Make and document build-vs-buy and architecture decisions as the product and team scale

●    Work directly with founders/engineering to translate ambiguous asks into scoped technical plans

Impact You’ll Have

●    Accelerate engineering velocity through scalable developer platforms and automation

●    Improve deployment reliability, platform uptime, and operational efficiency

●    Enable secure and scalable AI-driven cybersecurity workloads

●    Reduce operational overhead through infrastructure automation and self-service systems

●    Help establish enterprise-grade cloud and on-premise deployment capabilities

●    Enhance product resiliency, observability, and operational excellence

●    Shape the long-term platform architecture powering next-generation cybersecurity products

●    Enable rapid and secure delivery of critical security innovations to customers

Required Experience

●    4+ years hands-on Linux administration (RHEL-family strongly preferred — AlmaLinux, CentOS, RHEL)

●    Deep Linux internals: systemd, networking, storage/LVM, process/resource management, kernel-level troubleshooting

●    Real AWS architecture experience — not just operating existing infra, but designing it (VPC, EC2, IAM, security groups, networking)

●    Demonstrated ability to scope and solve ambiguous problems independently, without a runbook or senior engineer to defer to

●    Scripting/automation proficiency (Python and/or Bash) beyond one-off scripts — built tooling that runs unattended

●    Track record of end-to-end ownership: has designed, built, and operated a system (not just contributed to one)

●    Clear, proactive communicator — documents decisions and explains reasoning without being asked

Required Skills & Qualifications

●    Strong Linux system administration and troubleshooting skills

●    Redhat certifications

●    Strong understanding of networking fundamentals, security, and distributed systems

●    Proficiency with Docker, and container orchestration

●    Experience with Terraform, Ansible, or similar infrastructure automation tools

●    Strong scripting or programming skills in Python, Bash, or Go

●    Knowledge of observability tools such as Prometheus, Grafana, ELK, or OpenTelemetry

●    Understanding of platform security best practices and secure infrastructure design

●    Familiarity with virtualization technologies and hybrid infrastructure environments

●    Strong problem-solving and debugging abilities

●    Excellent communication and collaboration skills

●    Ability to thrive in fast-paced startup environments

Nice to Have

●    Configuration management/automation at scale (Ansible, AWX, Terraform, or similar)

●    Monitoring/observability stack experience (Prometheus, Grafana, Zabbix, ELK, Datadog)

●    Container experience (Docker; Kubernetes a plus but not core to this VM-based stack)

●    Experience in a startup or small-team environment where infra was built from scratch

●    Security/compliance exposure (vulnerability remediation, hardening, SSO/access control)

The Mindset

Problem Solver

You thrive on complex, ambiguous challenges and engineer elegant solutions.

Ownership-Driven

You take initiative, move fast, and deliver outcomes without hand-holding.

Continuous Learner

You stay ahead of the curve in AI, ML, cloud-native technologies, and emerging infrastructure trends.

Startup DNA

You excel in fast-moving environments where priorities evolve and impact is immediate.

We are looking for a Lead DevOps Engineer with strong hands-on experience in AWS, GCP, CI/CD, Kubernetes, Docker, Terraform, Pulumi and DevSecOps. The candidate will lead DevOps teams, drive technical delivery with client stakeholders, design scalable and secure cloud infrastructure, and establish best practices for automation, deployment, reliability, and cost optimization across cloud environments.

### Key Responsibilities

* Lead and mentor DevOps engineers, drive technical execution, and ensure timely delivery of client requirements.

* Engage with client teams and architects to understand requirements, provide technical guidance, and drive solution design and implementation.

* Design, implement, and optimize CI/CD pipelines, GitOps workflows, and automated release processes.

* Architect and manage cloud infrastructure across AWS and GCP (Azure optional) using Infrastructure as Code.

* Lead containerization and orchestration initiatives using Docker, Kubernetes, and Helm.

* Drive DevSecOps, observability, SRE practices, disaster recovery, and cloud cost optimization.

* Troubleshoot complex production issues, drive root cause analysis, and ensure system reliability, security, and performance.

* Collaborate with Development, QA, Security, Architecture, and client teams to drive engineering standards and continuous improvement.

### Mandatory Skills

* 7-9 years of experience in DevOps, Cloud Engineering, or Platform Engineering, including team leadership and client-facing responsibilities.

* Strong hands-on experience with AWS and GCP, including cloud infrastructure, networking, security, and managed services.

* Expertise in CI/CD tools such as Jenkins, Azure DevOps, GitLab CI/CD, GitHub Actions, or equivalent platforms.

* Strong experience with Docker, Kubernetes, Helm, and managed Kubernetes services such as AKS, EKS, or GKE.

* Hands-on expertise in Terraform and Ansible, with experience in Infrastructure as Code and configuration management.

* Experience with GitOps practices and tools such as Argo CD or Flux.

* Strong understanding of Git, branching strategies, release management, and deployment automation.

* Experience implementing DevSecOps practices, including security scanning, secrets management, and vulnerability management.

* Experience with monitoring, logging, alerting, production troubleshooting, and root cause analysis.

* Proficiency in Linux administration, networking fundamentals, and Bash/Python/PowerShell scripting.

* Proven ability to lead teams, manage priorities, communicate with clients, and drive technical decisions independently.

independently.

### Preferred Skills

* Knowledge of SAST/DAST, SBOM, software supply chain security, and security policy enforcement.

* Experience with observability tools such as Prometheus, Grafana, ELK Stack, Datadog, or Splunk.

* Experience with cloud migrations, hybrid environments, disaster recovery, high availability, and cost optimisation.

* Knowledge of service mesh technologies such as Istio or Consul, and API gateways or application gateways.

* Experience with enterprise cloud security, IAM, network security, and infrastructure

Role Overview:

Virtana is seeking a Senior Manager, Global DevOps Engineering to lead the global team, platforms, and infrastructure that enable rapid, reliable product delivery. This leader will own DevOps strategy and execution across SaaS (GCP heavy, with presence in AWS and Azure) & on-premises Infrastructure, CI/CD, automation, reliability, security, and developer productivity, while aligning distributed teams and cross-functional stakeholders around measurable business outcomes.

Key Accountabilities:

• Strategy and Execution: Set the global DevOps roadmap and operating model, aligned with product, engineering, and business priorities.
• Global Leadership: Build, lead, and develop a high-performing team across geographies, with clear accountability and consistent engineering practices.
• Cloud and Platform Ownership: Own the architecture, reliability, security, scalability, and cost efficiency of global GCP and hybrid infrastructure.
• Software Delivery: Advance secure, standardized CI/CD, Infrastructure as Code, automation, and self-service capabilities to accelerate delivery and improve quality.
• Operational Excellence: Establish SLOs, observability, incident response, disaster recovery, governance and metrics for critical platforms. Own the global on-call program and serve as the escalation point for major incidents from SaaS Infra/DevOps side.
• Executive Partnership: Align stakeholders on priorities, investments, dependencies, and risk; communicate outcomes and tradeoffs to senior leadership.

Required Qualifications:  

• 15+ years in software engineering, infrastructure, cloud operations, or DevOps, including 5+ years leading senior or management-level teams.
• Proven success in leading global teams across geographies, cultures, and time zones.
• Deep expertise in GCP architecture, security, networking, reliability, and cost governance.
• Demonstrated ownership of enterprise CI/CD, build and release automation, and modern software delivery practices.
• Strong experience with Terraform or equivalent Infrastructure as Code, Kubernetes, containers, observability, SRE, and disaster recovery.
• Track record operating secure, resilient global infrastructure for fast-paced development and release environments.
• Daily hands-on use of AI tools (e.g., Claude) for IaC, CI/CD pipelines and incident response, with a record of driving AI adoption that improves delivery speed and quality.
• Executive-level communication and stakeholder leadership, with the ability to align priorities, resolve tradeoffs, and develop strong leaders.

About the role

You will be a pivotal member of the leadership team, responsible for driving the company's product and platform strategy while overseeing engineering excellence across AI, data, platform, DevOps and infrastructure. This is a mission-critical role for an engineering leader who is both strategic and hands-on, and who can build scalable technologies for global enterprise clients in a fast-paced innovation ecosystem.

Reports to: CEO · Location: Bengaluru, India — hybrid, 3 days a week in office

What you will do

Technology & product leadership

• Define and drive the technology vision, architecture and long-term platform roadmap.
• Oversee the architecture, design and delivery of highly scalable enterprise systems.
• Ensure engineering excellence, velocity and reliability across the product lifecycle.

Engineering & platform management

• Lead platform engineering, product technology, DevOps, infrastructure and Quality Engineering.
• Build robust cloud-native systems using the Azure, AWS and GCP ecosystems.
• Oversee operational effectiveness, including uptime, production reliability and cost optimisation.

Innovation & AI strategy

• Spearhead Mission AI by developing scalable, production-grade AI/ML and GenAI capabilities.
• Own the GenAI/LLM solutions architecture.
• Core specialisation in AI agents and autonomous workflows, data extraction and intelligent automation.
• Direct hands-on architectural oversight of large language models, applied AI and multi-layered deep learning products.
• Extensive expertise in building intelligent document automation systems — similar in complexity to patent parsing, legal workflow automation and structured decision intelligence tools.

Technical leadership

• A proven track record overseeing product architecture, tech strategy and cross-functional engineering execution across core full-stack and AI platforms.
• Collaborate with executive leadership on business strategy, client requirements and product delivery.
• Build, mentor and scale high-performing engineering teams with a growth mindset.
• Establish a strong technology culture grounded in ownership, innovation and continuous learning.

What success looks like

• Mission AI: build a world-class AI system leveraging GenAI, ML and enterprise-grade data engineering.
• Hyper-scaling: architect and scale the platform to match global industry leaders in the IP space.
• Culture building: develop a strong engineering organisation with high ownership, performance and innovation DNA.

Qualifications & experience

• Preferably under 15 years of enterprise software engineering experience across B2B SaaS or technology-first companies; fewer is fine for an exceptional engineer.
• A proven track record of taking early-stage AI/ML prototypes and scaling them into robust enterprise SaaS platforms featuring multi-agent orchestration, complex workflows and decision intelligence.
• Experienced in building and mentoring agile, lean startup teams of full-stack and machine learning engineers from the ground up.
• Proven leadership in defining and executing technology strategy and platform roadmaps.
• Extensive cloud-native engineering experience with Azure, AWS and GCP.

Technical expertise

• Strong full-stack engineering background (Java, Python, JavaScript frameworks).
• Expertise with JS frameworks such as React, Angular and Node.js.
• Experience building and scaling distributed systems and microservices.
• Strong knowledge of databases (SQL, NoSQL), data modelling and unstructured data management.
• Strong understanding of Agile methodologies and tools (Atlassian, Git, CI/CD pipelines).

Behavioural & leadership competencies

• Product and delivery management expertise, end to end, including delivery and customer support.
• Excellent communication, with the ability to influence executive stakeholders.
• High technical proficiency combined with strong business acumen.
• Strong analytical and decision-making skills.

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.

TECHJAYS

THE AI REIMAGINATION COMPANY

Position DevOps Lead

Experience 10+ Years

Location Coimbatore / Hybrid

Joining Immediate / ASAP

Primary SkillsDevOps, AWS or Azure, CI/CD, Kubernetes, Docker, Terraform, Linux, Git, Cloud Infrastructure, Infrastructure Automation, Monitoring & Observability

Preferred SkillsAI/ML Infrastructure Exposure, GenAI Applications, GitOps, Argo CD, Prometheus, Grafana, Python, Bash, PowerShell, Cloud Security, FinOps

About Techjays

At Techjays, we're helping businesses reimagine how they build, operate, and scale with AI at the core. We focus on developing secure, scalable, production-grade AI systems that solve complex business challenges and deliver measurable business outcomes.

Our team brings together experienced engineers and technology leaders from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We work with global clients to build advanced AI-powered applications, enterprise platforms, and intelligent automation solutions.

We're looking for a DevOps Lead who can take ownership of cloud infrastructure, deployment automation, CI/CD pipelines, platform reliability, and engineering operations.

The ideal candidate will have deep hands-on expertise in either AWS or Azure, along with strong experience in Kubernetes, containerization, Infrastructure as Code, and production cloud environments.

You will lead the design and implementation of reliable infrastructure platforms, establish DevOps best practices, and work closely with software engineering and AI teams to support the deployment and operation of modern applications.

This role requires a strong hands-on cloud and DevOps specialist who can architect, implement, troubleshoot, and optimize production infrastructure. Prior exposure to AI/ML or AI-enabled applications is required, but specialized MLOps expertise is not mandatory.

Key Responsibilities

1. Cloud Infrastructure & Architecture

• Lead the design, implementation, and management of scalable, secure, and highly available cloud infrastructure.
• Own cloud infrastructure architecture and operations across AWS or Azure.
• Design and manage cloud environments covering compute, networking, storage, databases, and container platforms.
• Establish infrastructure standards, architecture patterns, and operational best practices.
• Manage cloud resource provisioning, configuration, scaling, and environment management.
• Ensure infrastructure meets requirements for availability, performance, security, and reliability.
• Drive infrastructure improvements through automation and continuous optimization.

2. DevOps & CI/CD Engineering

• Design, implement, and maintain CI/CD pipelines for application development and deployment.
• Manage multi-stage deployment workflows across development, testing, staging, and production environments.
• Implement automated build, testing, deployment, and release processes.
• Establish reusable pipeline templates, deployment standards, and approval workflows.
• Manage deployment strategies, including rolling, blue/green, and canary deployments.
• Implement rollback mechanisms and ensure reliable production releases.
• Integrate CI/CD workflows with source control, artifact repositories, and container registries.
• Continuously improve deployment efficiency, release reliability, and engineering productivity.

3. Containerization & Kubernetes Management

• Architect and manage containerized application environments using Docker and Kubernetes.
• Manage production Kubernetes clusters using Amazon EKS or Azure AKS.
• Implement Kubernetes configurations covering deployments, services, networking, secrets, storage, and resource management.
• Work with Helm charts for application packaging and deployment.
• Optimize container resource utilization, application scaling, and cluster performance.
• Troubleshoot complex container and Kubernetes-related production issues.
• Establish best practices for container security and workload reliability.

4. Infrastructure as Code & Automation

• Implement Infrastructure as Code using Terraform and cloud-native provisioning tools.
• Automate infrastructure provisioning, configuration management, and environment setup.
• Develop reusable infrastructure modules and deployment automation workflows.
• Use Python, Bash, or PowerShell to automate operational tasks and improve efficiency.
• Reduce manual intervention through standardization and automation.
• Maintain infrastructure documentation, configuration standards, and version-controlled deployment workflows.

5. Monitoring, Reliability & Production Operations

• Establish centralized monitoring, logging, alerting, and observability across cloud environments.
• Implement monitoring solutions using CloudWatch, Azure Monitor, Prometheus, Grafana, or equivalent platforms.
• Monitor application availability, infrastructure health, resource utilization, and system performance.
• Lead troubleshooting and resolution of complex production incidents.
• Conduct root cause analysis and implement permanent corrective actions.
• Establish operational practices for backup, disaster recovery, availability, and business continuity.
• Improve system reliability through proactive monitoring and performance optimization.

6. Cloud Security & Governance

• Implement cloud security best practices across infrastructure and application environments.
• Manage IAM, RBAC, access controls, service identities, and secrets management.
• Secure cloud networking, virtual networks, firewalls, and infrastructure access.
• Implement container security and infrastructure hardening practices.
• Ensure cloud environments follow organizational security and compliance requirements.
• Identify infrastructure vulnerabilities and coordinate remediation activities.
• Establish secure deployment and configuration management practices.

7. AI Infrastructure & Engineering Collaboration

• Work closely with AI/ML and software engineering teams to provide infrastructure for AI-powered applications.
• Support the deployment and operation of LLM-based applications, AI services, and AI-enabled platforms.
• Design cloud infrastructure capable of supporting AI workloads, including compute, storage, networking, and containerized services.
• Support the infrastructure requirements of AI applications across development, testing, and production environments.
• Collaborate with engineering teams to improve deployment reliability, scalability, and operational performance of AI-powered systems.
• Evaluate infrastructure technologies and tools that support evolving AI application requirements.

8. Technical Leadership & Team Development

• Provide technical leadership to DevOps engineers and guide implementation across projects.
• Establish engineering standards, infrastructure best practices, and operational procedures.
• Mentor team members on cloud architecture, automation, CI/CD, Kubernetes, and production operations.
• Lead technical discussions and make architecture decisions involving infrastructure and DevOps technologies.
• Collaborate with engineering, security, and product teams to align infrastructure capabilities with business requirements.
• Drive continuous improvement across DevOps processes, tools, and engineering practices.

Required Technical Skills & Experience

1. Cloud Platforms

• 10+ years of overall experience in DevOps, cloud infrastructure, or platform engineering.
• Strong hands-on expertise in at least one major cloud platform: AWS or Azure.
• Practical experience designing, deploying, and operating production-grade cloud infrastructure.

AWS: EC2, S3, IAM, VPC, EKS, Lambda, ECR, CloudWatch, and related infrastructure services.

Azure: Azure Virtual Machines, VNets, AKS, Azure DevOps, Azure Container Registry, Azure Monitor, Key Vault, and related infrastructure services.

Candidates do not need to be experts in both AWS and Azure. Deep expertise in either platform is the priority.

2. DevOps & CI/CD

• Strong experience designing and maintaining CI/CD pipelines.
• Hands-on experience with Azure DevOps, Jenkins, GitHub Actions, GitLab CI, or equivalent tools.
• Understanding of multi-stage pipelines, automated deployments, release approvals, and artifact management.
• Experience implementing deployment automation and rollback strategies.
• Strong understanding of Git workflows and version control practices.

3. Containers & Kubernetes

• Strong hands-on experience with Docker and Kubernetes.
• Practical experience managing EKS or AKS environments.
• Understanding of Kubernetes networking, scaling, storage, secrets, and workload management.
• Experience with Helm and container orchestration.
• Ability to troubleshoot production container and Kubernetes environments.

4. Infrastructure as Code & Scripting

• Strong experience with Terraform and Infrastructure as Code practices.
• Familiarity with CloudFormation, Bicep, ARM templates, or similar tools.
• Working knowledge of Python, Bash, or PowerShell for infrastructure automation.
• Strong understanding of Linux administration and system troubleshooting.

5. Monitoring & Reliability Engineering

• Experience implementing infrastructure and application monitoring.
• Familiarity with CloudWatch, Azure Monitor, Prometheus, Grafana, and centralized logging solutions.
• Understanding of incident management, root cause analysis, performance optimization, and system availability.
• Experience establishing alerting, operational dashboards, and reliability practices.

6. AI/ML Infrastructure Exposure

• Prior experience supporting AI/ML applications, Generative AI platforms, LLM applications, or AI-enabled products.
• Understanding of infrastructure requirements for deploying and operating AI-powered applications.
• Familiarity with containerized AI services, cloud-based model integrations, and scalable application environments.

Note: This role does not require specialized MLOps expertise or model development experience. Strong cloud and DevOps engineering fundamentals remain the primary requirement.

Preferred Skills

• Experience implementing GitOps workflows using Argo CD or similar tools.
• Experience with blue/green deployments, canary releases, and automated rollback mechanisms.
• Exposure to cloud security, enterprise networking, governance, and landing-zone architecture.
• Experience with cloud cost optimization and FinOps practices.
• Familiarity with AI/ML infrastructure and production GenAI applications.
• Experience with Python-based automation and infrastructure tooling.
• Relevant AWS, Azure, Kubernetes, or Terraform certifications.

What We're Looking For Beyond Skills

• Cloud Expertise: Deep technical specialization in AWS or Azure, with the ability to design and manage production infrastructure independently.
• Hands-on Engineering: Someone who actively builds, automates, troubleshoots, and improves infrastructure rather than focusing only on team management.
• Technical Ownership: Takes responsibility for infrastructure reliability, deployment quality, security, and operational performance.
• System Thinking: Understands how cloud infrastructure, applications, networking, databases, and deployment pipelines work together.
• Problem-Solving: Ability to diagnose complex production issues and implement long-term engineering solutions.
• Automation Mindset: Continuously identifies opportunities to eliminate manual work and improve operational efficiency.
• Technical Leadership: Can mentor engineers, establish best practices, and drive technical decisions.
• AI Readiness: Has practical exposure to supporting AI-powered applications and understands their infrastructure requirements.
• Collaboration: Works effectively with software engineering, AI/ML, security, and product teams.

Typical Technology Environment

AreaTechnologiesCloud PlatformsAWS, AzureCI/CDAzure DevOps, GitHub Actions, Jenkins, GitLab CIContainersDocker, Kubernetes, EKS, AKS, HelmInfrastructure as CodeTerraform, CloudFormation, Bicep, ARMGitOpsArgo CD, Git-based deployment workflowsMonitoring & ObservabilityCloudWatch, Azure Monitor, Prometheus, GrafanaAutomationPython, Bash, PowerShellOperating SystemsLinux, WindowsSecurityIAM, RBAC, Secrets Management, Network SecurityAI ExposureAI/ML Applications, GenAI, LLM Platforms, AI-enabled Products

What We Offer

• Competitive compensation aligned with experience and expertise.
• Coimbatore office-based work environment with hybrid flexibility.
• Opportunity to lead cloud infrastructure and DevOps engineering for global clients.
• Exposure to modern AWS/Azure, Kubernetes, automation, and AI engineering practices.
• Paid holidays and flexible time off.
• Medical insurance covering self and family, up to ₹4 lakh per person.
• Opportunities to influence infrastructure architecture and engineering practices.
• A culture that values clarity, integrity, ownership, and continuous growth.

Join Techjays

If you're passionate about building reliable cloud platforms, automating complex infrastructure, and leading DevOps engineering for modern AI-powered applications, we'd love to hear from you.

 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