Cloud & AI Platform Engineer at Ampera Technologies · Bengaluru (Bangalore), Chennai · 4 - 10 years · Profitable · Posted 22 Jun 2026

Job Description:
We are seeking a Cloud & AI Platform Engineer to design and operate AI-native infrastructure that supports large-scale machine learning, generative AI, and agentic AI systems.
This role will focus on building secure, scalable, and automated multi-cloud platforms across AWS, Azure, GCP, and hybrid on-prem environments, enabling teams to deploy LLMs, AI agents, and data-driven applications reliably in production.
You will work at the intersection of cloud engineering, MLOps, LLMOps, DevOps, and data infrastructure, helping build platforms that support RAG pipelines, vector search, AI model lifecycle management, and AI observability.
Key Responsibilities
AI & Agentic Infrastructure
- Design infrastructure to support agentic AI systems, autonomous agents, and multi-agent workflows.
- Build scalable runtime environments for LLM orchestration frameworks.
- Enable deployment of AI copilots, assistants, and autonomous decision systems.
Common frameworks may include:
- LangChain
- LlamaIndex
- AutoGPT
LLMOps & AI Model Lifecycle
Design and manage LLMOps pipelines for the full lifecycle of large language models:
- Model deployment
- Prompt management
- Versioning
- Evaluation and testing
- Model monitoring
Integrate with AI platforms such as:
- Azure Machine Learning
- Amazon SageMaker
- Vertex AI
Retrieval-Augmented Generation (RAG) Infrastructure
Design and optimize RAG pipelines that integrate enterprise knowledge with LLMs.
Responsibilities include:
- Document ingestion pipelines
- Embedding generation workflows
- Knowledge indexing
- Query orchestration
- Retrieval optimization
- Support scalable semantic search architectures.
Vector Database & Knowledge Infrastructure
Deploy and manage vector databases used for AI applications and semantic retrieval.
Common technologies include:
- Pinecone
- Weaviate
- Milvus
- FAISS
Responsibilities include:
- Index optimization
- Query latency tuning
- Scalable embedding storage
- Hybrid search architecture
Multi-Cloud AI Infrastructure
Design and maintain AI-ready infrastructure across:
- Amazon Web Services
- Microsoft Azure
- Google Cloud Platform
Key responsibilities include:
- GPU infrastructure management
- Distributed training environments
- Hybrid cloud integrations with on-prem data centers
- Infrastructure scaling for AI workloads
Data Platforms & Integration
- Support deployment and optimization of data lakes, data warehouses, and streaming platforms.
- Work with data engineering teams to ensure secure and scalable data infrastructure.
Cloud Architecture & Infrastructure
- Design and implement scalable multi-cloud infrastructure across Azure, AWS, and Google Cloud.
- Build hybrid cloud architectures integrating on-premise environments with cloud platforms.
- Implement high availability, disaster recovery, and auto-scaling architectures for AI workloads.
DevOps, Platform Engineering & Automation
Build automated cloud infrastructure using modern DevOps practices.
Tools may include:
- Terraform
- Docker
- Kubernetes
- GitHub Actions
Responsibilities include:
- Infrastructure as Code (IaC)
- Automated deployments
- CI/CD pipelines for AI models and services
- Platform reliability and scalability
AI Observability & Monitoring
Implement observability frameworks to monitor AI systems in production.
This includes:
- Model performance monitoring
- Prompt evaluation
- Hallucination detection
- Latency and throughput analysis
- Cost monitoring for LLM usage
Tools may include:
- Arize AI
- WhyLabs
- Weights & Biases
Security, Governance & Responsible AI
Ensure AI systems follow strong governance and security practices.
Responsibilities include:
- Data privacy and compliance
- Model governance frameworks
- Secure model deployment
- Monitoring model bias and drift
- AI risk management
Support enterprise frameworks for Responsible AI and AI compliance.
Data & Security
- Experience with data lake architectures, distributed storage, and ETL pipelines
- Knowledge of data security, encryption, IAM, and compliance frameworks
- Familiarity with AI governance and responsible AI practices
Required Skills
Cloud & Infrastructure
- Strong experience in Azure (must have), AWS or GCP
- Hybrid and multi-cloud architecture
- GPU infrastructure management
DevOps & Automation
- Kubernetes
- Docker
- Terraform
- CI/CD pipelines
AI / ML Platforms
- MLOps pipelines
- Model deployment
- Model monitoring
AI Application Infrastructure
- Vector databases
- RAG pipelines
- LLM orchestration frameworks
Programming
Experience in one or more languages:
- Python
- Go
- Java
- TypeScript
Preferred Qualifications
- Experience building AI copilots or autonomous agents
- Knowledge of distributed model training - Knowledge of GPU infrastructure and distributed training
- Familiarity with AI evaluation frameworks - Familiarity with model monitoring, drift detection, and AI observability
- Experience building enterprise AI platforms
Education & Experience
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
- 4–8+ years experience in cloud infrastructure, DevOps, or platform engineering
- Experience working in data-driven or AI-focused environments
What Success Looks Like
- Reliable ML model deployment pipelines - Reliable infrastructure for LLMs and AI agents, Scalable RAG knowledge platforms
- Efficient multi-cloud infrastructure management - Fast deployment cycles for AI products
- Secure and scalable AI-ready cloud platforms
- Strong automation and governance across cloud and AI systems

About Ampera Technologies
About
At Ampera Technologies, we empower businesses with cutting-edge data analytics, quality assurance, and data engineering solutions
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Job Description: Lead - Cloud Engineering (AWS / Azure)
Role Title: Lead - Cloud Engineering
Experience Level: 10+ Years
Domain Focus: Healthcare AI & Cloud Infrastructure
Location: Remote
Job Overview
We are seeking an experienced Lead - Cloud Engineering with over 10 years of IT experience to lead our cloud strategy, architecture, and infrastructure teams. In this role, you will oversee end-to-end cloud deployment, multi-cloud migration, and scalable architecture designed to support cutting-edge Generative AI applications in the healthcare technology domain.
The ideal candidate brings deep technical expertise in both AWS and Azure, strong hands-on capability in cloud infrastructure, and proven leadership experience driving security, compliance, and team growth.
Key Responsibilities
Cloud Architecture & Migration
- Lead the architecture, design, and execution of cloud migrations, deployments, and modernizations across AWS and Azure environments.
- Drive Infrastructure as Code (IaC) standards using Terraform, CloudFormation, or Bicep to ensure scalable, automated infrastructure provisioning.
- Build high-availability, low-latency architectures optimized for data-intensive Generative AI and Machine Learning workloads.
Security & Healthcare Compliance
- Enforce healthcare security standards including HIPAA, HITRUST, SOC 2, and data governance best practices across all cloud assets.
- Implement Zero-Trust security, Identity Access Management (IAM), data encryption key management, and continuous vulnerability monitoring.
Leadership & Team Management
- Manage, mentor, and scale a high-performing team of DevOps, Cloud, and SRE Engineers.
- Drive Agile workflows, sprint planning, incident response frameworks, and SLA compliance.
- Collaborate closely with Data Engineering, AI/ML, and Software Product teams to align infrastructure with business roadmaps.
Operations & FinOps
- Establish cloud cost optimization strategies (FinOps) to manage computing costs associated with AI models and large-scale data processing.
- Manage monitoring, alerting, and telemetry frameworks (e.g., Prometheus, Datadog, CloudWatch) to ensure 99.99% uptime.
Key Requirements
- Experience: 10+ years of overall IT experience with at least 5+ years in a cloud leadership or lead architect role.
- Cloud Platforms: Advanced hands-on expertise with both AWS (e.g., EC2, S3, EKS, Bedrock, SageMaker) and Azure (e.g., AKS, Azure OpenAI, Blob, Virtual Machines).
- DevOps & IaC: Strong background in Terraform, Docker, Kubernetes, CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins).
- Domain Knowledge: Prior experience building or managing cloud environments within Healthcare, Life Sciences, or HealthTech is strongly preferred.
- AI/ML Familiarity: Experience supporting cloud infrastructure for machine learning pipelines, LLM deployments, or GPU compute management.
- Certifications (Preferred): AWS Certified Solutions Architect – Professional, Azure Solutions Architect Expert, or Certified Kubernetes Administrator (CKA).
Tasks & Responsibilities: (Major task and role person will have to perform – list all the relevant points)
Together with the Business Cloud Services team, you will design, deploy, and operate a cloud‑native Kubernetes PaaS platform on Azure, ensuring high availability, security, and operational excellence.
Your main duties include:
· Drive cloud‑native automation and self‑service capabilities, ensuring platform security, availability, and disaster recovery readiness
· Design, operate, and continuously improve Kubernetes clusters and PaaS environments on Azure / AKS
· Collaborate closely with development teams on deployment strategies, operational requirements, and platform integration
· Review and maintain infrastructure‑as‑code configurations, CI/CD pipelines, and cloud‑native deployments
· Build and maintain CI/CD pipelines using Azure DevOps
· Implement and operate infrastructure‑as‑code solutions using Terraform, Helm, and Ansible
· Manage containerized workloads and orchestration across cloud‑native environments
· Set up, operate, and enhance monitoring, logging, and alerting stacks using tools such as Prometheus and Grafana
· Coordinate with support teams on platform incidents, escalations, and post‑incident analysis
· Contribute to incident response, continuous improvement, and operational stability
· Support the development and refinement of DevOps practices, runbooks, and operational standards
· Actively contributes to improving developer experience and platform reliability
Education & Trainings + Certifications: (Basic & Professional)
· Bachelor’s degree (Preferably engineering graduate)
· Azure Solutions Architect Expert Certification is a plus.
· (optional) ITIL Foundation
Technical know-how: (Mention the technology on which person must be experienced)
Mandatory
o Bachelor’s degree in computer science, Information Systems, or a related field
o 5+ years of relevant professional experience in DevOps, Cloud Engineering, or Platform Engineering roles
o Strong Linux system administration skills for operating production‑grade cloud‑native platforms
o Proven experience with Microsoft Azure, including AKS and Azure DevOps tooling
o Strong expertise in Kubernetes, including cluster operations, RBAC, networking, and storage
o Hands‑on experience with container technologies such as Docker and container registries
o Proficiency with Terraform, Helm, Ansible, and PowerShell
o Experience building and operating CI/CD pipelines using Azure DevOps or equivalent tools
o Cloud‑native monitoring and observability experience using Prometheus, Grafana, and alerting pipelines
o Solid understanding of security and compliance requirements such as PCI DSS and SOC2
o Scripting skills for automation and tooling (Bash, Python, PowerShell)
o Practical experience using Git for version control
o Excellent communication skills in English (Spanish is a plus)
o Automation‑first mindset and strong collaboration skills within Agile teams
Good to know
Principles of Agile Software Development.
· GitHub Actions, GitLab CI, Jenkins, Azure DevOps
· Containers: Docker, Kubernetes (EKS / AKS / GKE)
· Configuration Management: Ansible
Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience).
3+ years of hands-on experience with Microsoft Azure, including IaaS, PaaS, networking, identity (Entra ID), and governance services.
2+ years of experience with DevOps tooling and practices, including CI/CD pipelines (Azure DevOps or GitHub Actions), Infrastructure as Code (Terraform, Bicep, or ARM), and version control (Git).
2+ years' experience in infrastructure design, platform engineering, or architecture.
Strong proficiency with automation and scripting — PowerShell, Azure CLI, Python, or Bash.
Solid understanding of containerisation (Docker) and familiarity with orchestration platforms (Azure Kubernetes Service).
Deep understanding of cloud architecture, deployment patterns, and management best practices, including the Azure Well-Architected Framework.
Experience defining standards, governance frameworks, and reference architectures for cloud platform consumption.
Strong knowledge of networking concepts, storage configurations, virtualisation technologies, and disaster recovery/backup design for hybrid environments.
Experience with Azure DevOps (Repos, Pipelines, Boards, Artifacts) or equivalent platforms.
Familiarity with identity and access management (IAM), including Entra ID, RBAC, PIM.
Strong understanding of security, compliance requirements, and IT governance frameworks (ITIL, COBIT, or similar).
Preferred
🚀 Hiring: Senior Azure Platform Engineer | Azure | Terraform | Kubernetes
📍 Location: India
💼 Employment: Full-Time | Long-Term
🎯 Experience: 10+ Years | 8+ Years Hands-on Azure
🔑 What We’re Looking For
▪️ Strong expertise in Azure Cloud Platform & Landing Zone Architecture
▪️ Advanced hands-on experience with Terraform & reusable IaC modules
▪️ Expertise in Kubernetes, Helm & container platforms
▪️ Strong understanding of Azure Networking, Entra ID, RBAC & Azure Policy
▪️ Experience with GitHub, GitHub Actions / Azure Pipelines & CI/CD
▪️ Hands-on GitOps & ArgoCD experience
▪️ Strong observability skills with Prometheus, Grafana & Azure Monitor
▪️ Experience designing and supporting microservices architectures
▪️ Knowledge of security, policy-as-code and IaC security scanning
▪️ Exposure to Azure Arc / Azure Local / Azure Stack HCI is a plus
Title : Senior AI Platform / MLOps Engineer
Experience : 6+ years
Work type : Chennai - Work from Office/other locations - Remote
Employment Type : Full Time
Notice Period : Immediate
Work Day :Mon to Fri
Key Responsibilities:
- Install, configure and operate OpenShift, NVIDIA GPU operator, OpenShift AI, and NIM microservices on 12× RTX PRO 6000 across two servers; single-node and HA control-plane topologies
- Serving configuration and tuning: quantized model deployment (FP8/FP4), replica balancing, batching, KV-cache and context management
- Azure GPU build environments: provisioning, cost control, parity with the on-prem stack via pinned container/model versions; cloud-to-factory migration with parity regression
- GitOps CI/CD, container registry, artifact/model versioning, environment promotion; observability and audit wiring (Splunk, Prometheus/Grafana)
- Benchmark automation: load harness, p50/p95/p99 latency, tokens/sec, GPU utilization; the capacity report data pipeline
- Platform upgrade procedure with evaluation-regression gates; deployment runbook as a first-class deliverable
Technical Skills:
- 6+ years infrastructure/platform engineering with 3+ years production Kubernetes; OpenShift experience strongly preferred
- Hands-on GPU inference serving in production: NIM, Triton, vLLM, or TensorRT-LLM — you have sized, deployed, and tuned LLM serving on real GPUs and can talk memory-bandwidth trade-offs
- GitOps fluency (ArgoCD/Flux), infrastructure-as-code, container internals; comfortable in air-gapped/proxy-restricted enterprise networks
- Observability depth: metrics, traces, log pipelines; has built performance test harnesses, not just run them
- Azure or AWS GPU compute operations experience
Strongly preferred
- NVIDIA GPU operator and AI Enterprise stack specifics; KServe; Milvus or pgvector operations; VAST/NFS/S3 storage integration; banking or other regulated-environment delivery
About Ampera:
Ampera Technologies, a purpose driven Digital IT Services with primary focus on supporting our client with their Data, AI / ML, Accessibility and other Digital IT needs. We also ensure that equal opportunities are provided to Persons with Disabilities Talent. Ampera Technologies has its Global Headquarters in Chicago, USA and its Global Delivery Center is based out of Chennai, India. We are actively expanding our Tech Delivery team in Chennai and across India. We offer exciting benefits for our teams, such as 1) Hybrid and Remote work options available, 2) Opportunity to work directly with our Global Enterprise Clients, 3) Opportunity to learn and implement evolving Technologies, 4) Comprehensive healthcare, and 5) Conducive environment for Persons with Disability Talent meeting Physical and Digital Accessibility standards
- Strong hands-on experience in Microsoft Azure Cloud.
- Good understanding of Azure services such as Compute, Storage, Event Hub, Event Subscription, Storage Queue, and PaaS services.
- Basic understanding of Azure AI Foundry and AI-related Azure service setup.
- Good Azure networking basics: VNet, subnet, routing, and basic troubleshooting.
- Strong knowledge of Terraform, especially:
- Terraform state
- plan / apply
- troubleshooting failures
- migration risks
- Terraform Enterprise concepts
- Strong Python coding capability, not just basic scripting.
- Experience using Python for API integration, automation, JSON/YAML handling, and internal tooling.
- Good understanding of CI/CD pipelines.
- Ability to troubleshoot pipeline failures.
- Comfortable with YAML and JSON.
- Ability to troubleshoot Azure infrastructure/platform issues.
- Ability to collect logs/evidence and coordinate with network/app/Microsoft support teams.
- Basic awareness of agentic AI / LLM concepts.
- Awareness of security and cost best practices.
Good to Have Skills
- Hands-on experience with Harness.
- Hands-on experience with Terraform Enterprise.
- Exposure to LangGraph / LangChain.
- Exposure to agentic AI workflows or skill creation.
- Exposure to Claude or enterprise LLM integrations.
- Knowledge of Azure ML Workspace, model registry, and managed endpoints.
- MLOps / LLMOps knowledge.
- FinOps / Azure cost optimization experience.
- Azure certifications: AZ-104, AZ-305, AZ-400, AZ-500.
Screening Priority:
Azure Cloud + Terraform + Python Coding + CI/CD Troubleshooting + YAML/JSON + Basic Agentic AI Awareness
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.
WowPe is a leading fintech company revolutionizing the way businesses handle financial transactions. Our suite of innovative products includes a secure Payment Gateway for seamless online transactions, robust Payouts solutions to streamline bulk payments, and a versatile Point of Sale (POS) system for efficient in-store transactions. At WowPe, we’re dedicated to providing user-friendly, scalable, and reliable solutions that empower businesses to grow and succeed in today’s fast-paced digital economy.
We are looking for a highly skilled Cloud Infrastructure & Cloud Network Engineer to design, build, and manage secure, scalable hybrid cloud environments at WowPe. This role will focus on cloud networking, hybrid connectivity, infrastructure automation, security, reliability, and performance across on-prem and cloud platforms (AWS/Azure). You will play a critical role in ensuring high availability, security, and performance of our fintech platforms.
A Day in the Life
- Design and review cloud network architectures (VPC/VNet, routing, segmentation)
- Troubleshoot latency, connectivity, VPN, and performance issues
- Work with DevOps and application teams to support deployments and scalability
- Automate infrastructure provisioning and security guardrails
- Monitor network health, traffic flow, and system performance
- Ensure security, compliance, and disaster recovery readiness
- Support hybrid connectivity between on-prem data centers and cloud environments.
Key Responsibilities
Cloud Networking & Hybrid Architecture
- Design and implement VPC/VNet architectures, subnetting, routing tables, NAT, gateways, and secure segmentation
- Build and manage hybrid connectivity between on-prem data centers and cloud using Site-to-Site VPN, ExpressRoute, Direct Connect
- Configure and manage Layer 4 & Layer 7 load balancers for high availability and traffic distribution
- Architect DNS, CDN, and edge networking strategies for low-latency global access
Security & Zero-Trust
- Implement Zero-Trust networking using security groups, NACLs, identity-aware proxies, mTLS
- Design secure access controls and network isolation
- Work closely with security teams to ensure PCI, ISO, SOC compliance readiness
Automation, Platform & Reliability
- Automate infrastructure provisioning using Infrastructure as Code (Terraform/ARM/CloudFormation)
- Build self-healing, auto-scaling architectures with health checks and fault tolerance
- Support and manage Kubernetes clusters (EKS/AKS) including networking and service communication
- Integrate infra with CI/CD pipelines for safe and frequent deployments
Operations & Observability
- Perform advanced troubleshooting for latency, packet loss, MTU, routing loops
- Implement and manage monitoring, logging, and observability (Prometheus, Grafana, ELK, Azure Monitor, CloudWatch)
- Design and maintain disaster recovery architectures, multi-region networking, and replication strategies
- Ensure high availability, performance optimization, and cost efficiency
Basic Qualifications & Skills
- 4+ years of experience in Cloud Infrastructure & Cloud Networking
- Strong hands-on experience with AWS and/or Azure
- Deep understanding of VPC/VNet, routing, NAT, gateways, load balancers, DNS
- Experience with Hybrid connectivity (VPN, ExpressRoute, Direct Connect)
- Solid knowledge of network security, firewalls, access control, segmentation
- Hands-on experience with Infrastructure as Code (Terraform preferred)
- Experience in monitoring, troubleshooting, and incident handling
- Strong understanding of high availability, DR, and performance optimization
Preferred Qualifications
- Experience in fintech, BFSI, or high-compliance environments
- Exposure to Zero-Trust architecture and security best practices
- Experience with Kubernetes (EKS/AKS), service mesh, microservices networking
- Familiarity with CI/CD pipelines and DevOps practices
- Knowledge of CDN, edge networking, and global traffic management
- Experience with compliance frameworks (PCI-DSS, ISO 27001, SOC2)
- Ability to design large-scale, resilient, production-grade architectures
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.
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










