AWS DevOps+MLOps Engineer

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).

• Bachelor’s degree in computer science, Data Science, Information Systems, or a related field  
• 8-10 years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering  
• Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure  
• Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn  

Job Title: Java AWS Kubernetes DevOps AI/ML

Experience: 8–10 Years

The candidate should have at least 1 year of experience in AI/ML and hands-on experience with the below technologies:

Java

AWS

Kubernetes

DevOps

AI/ML

MongoDB / PostgreSQL

Key-Value Caching

Vector Databases – ChromaDB / Pgvector

 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

Greetings!

Hiring For Large Product Based Company!

Role- Mlops Engineer

Experience- 8-12 years

Location- Pune, Nagpur

JD-

• 8-10 years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering  
• Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure  

Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn  

Company Overview:

Planview is hiring a DevOps Engineer in Bengaluru, India to support Planview SaaS applications across the product line. You will work in a global, collaborative team — owning CI/CD pipelines, cloud infrastructure, and automation to keep deployments fast and systems reliable.

Responsibilities

• Build and maintain CI/CD pipelines in Jenkins for reliable, fast delivery.
• Manage containerized workloads on Docker and ECS — task definitions, services, and clusters.
• Provision and manage AWS infrastructure using Terraform (CloudFormation a plus).
• Automate configuration and deployment tasks using Python (Ansible a plus).
• Set up and maintain monitoring and alerting via New Relic (CloudWatch, Datadog, or Prometheus/Grafana a plus).
• Write Shell and Python scripts to automate operations and reduce manual work.
• Manage Git workflows — branching, merge strategies, and pull request reviews.
• Administer and support MSSQL databases underpinning the product line — backups, restores, and basic performance troubleshooting.
• Troubleshoot deployment, performance, and infrastructure issues with development teams.
• Participate in on-call rotations and drive incident response.
• Continuously improve infrastructure resilience and deployment speed.
• Apply AI-assisted engineering tools (e.g., GitHub Copilot, Claude Code) to speed up IaC authoring, pipeline debugging, and day-to-day scripting.

Qualifications

Must-Have Skills

• Experience: 4–6 years of experience in DevOps, SRE, or Infrastructure Engineering.
• OS: Windows administration (systemd, package management, log analysis).
• Cloud: AWS (Active Directory, ECS, EC2, CloudFront, S3, VPC, IAM, RDS, Lambda basics).
• Source Control: Git — branching, merge/rebase, PR reviews.
• CI/CD (Jenkins): Pipeline creation and basic Groovy scripting.
• Containerization (Docker + ECS): Task definitions, services, and clusters.
• IaC: Terraform.
• Monitoring: New Relic.
• Scripting: Bash and Python scripting for automation.
• Networking Basics: DNS, load balancers, security groups, VPNs.
• Logging: ELK stack / CloudWatch Logs.
• Database: MSSQL administration — backups, restores, basic performance troubleshooting.
• Infrastructure Automation: Hands-on experience automating infrastructure provisioning, configuration, and deployment end-to-end.
• AI-Assisted Engineering: Comfortable working with AI coding/DevOps assistants (e.g., GitHub Copilot, Claude Code) for IaC generation, scripting, and troubleshooting — verified via a mandatory AI proficiency assessment during interviews.

Nice-to-Have Skills

•     Configuration Management: Ansible.

•     Additional IaC: CloudFormation.

•     Architecture: Knowledge of microservices architecture.

•     Cloudflare: DNS, CDN, WAF.

•     Artifact Repositories: Nexus, JFrog Artifactory, ECR.

•     Other CI/CD Tools: GitHub Actions.

•     AWS cost optimization / FinOps awareness.

•     Datadog, CloudWatch, or Prometheus/Grafana.

•     AIOps: Exposure to AI-driven anomaly detection, root-cause analysis, or incident triage (e.g., Dynatrace Davis AI, Datadog Bits AI, Harness AIDA).

•     Database Basics: RDS backups, restores, performance tuning.

Role Overview

• Role: Senior DevOps / CloudOps Engineer
• Domain: IoT Smart Controls & Building Management Systems (BMS) Platform
• Environment: Scale-Up product ecosystem demanding Startup Agility

Key Responsibilities

• Cloud & Infrastructure Management: Design, provision, and maintain secure, highly available cloud infrastructure (AWS/Azure/GCP) with application of Infrastructure as Code capabilities(Terraform/Ansible)
• IoT & Real-Time Messaging Scalability: Manage high-throughput MQTT broker clusters and WebSocket communication layers to support massive concurrent device telemetry
• CI/CD Pipeline Operations: Build and optimize automated build, test, and deployment pipelines for heterogeneous micro-services spanning Java Spring Boot backends, PHP services, and containerized components.
• Container Orchestration: Manage Docker containers and Kubernetes clusters ensuring seamless micro-services orchestration, zero-downtime rollouts, and failover resilience.
• Monitoring & Observability: Implement comprehensive logging, tracing, and metric alerts (Prometheus, Grafana, ELK stack) across cloud components and edge-to-cloud communication paths.
• Cross-Functional Collaboration: Coordinate with firmware teams (C/C++) and mobile/web application teams (React Native, JavaScript, Android, iOS) to ensure smooth continuous integration and API gateway reliability

Required Skills & Qualifications

• Experience: 8+ years of hands-on cloud engineering and DevOps experience in production environments.
• Cloud & IaC: Deep proficiency in cloud platform administration (AWS/Azure) alongside Terraform.
• Networking & Protocols: Solid understanding of TCP/IP, DNS, load balancing, WebSockets, and MQTT broker scaling (e.g., EMQX, HiveMQ, or Mosquitto).
• Containerization Stack: Working knowledge of Docker, Kubernetes, and Helm charts.
• Scripting & Automation: Good scripting fundamentals in Python, Bash
• Tech Stack Familiarity: Operational awareness of Java Spring Boot, PHP, and JavaScript ecosystems to debug deployment bottlenecks and assist engineering teams.

Job Title : Senior AWS DevSecOps & AI Platform Engineer

Experience Required : 5+ Years in AWS / Cloud Engineering

Terraform Experience : 4+ Years

Location : Gurugram

Work Mode : Onsite

Employment Type : Full-time

About the Role :

We are looking for an experienced Senior AWS DevSecOps & AI Platform Engineer with strong expertise in AWS cloud infrastructure, Kubernetes, Infrastructure as Code (IaC), CI/CD automation, cloud security, and database administration.

The ideal candidate will be responsible for designing and maintaining secure, scalable, reliable, and cost-efficient cloud environments while supporting microservices-based applications and implementing DevSecOps best practices. The role also involves building and deploying AI agents using Amazon Bedrock and Bedrock AgentCore, along with managing enterprise development and collaboration tools.

Mandatory Skills :

AWS (EC2, EKS, ECS, Lambda, S3, CloudWatch), Kubernetes, Terraform, Jenkins, Bitbucket Pipelines, CI/CD, DevSecOps, AWS Security Services (IAM, WAF, GuardDuty, Security Hub, KMS, Secrets Manager), Microservices, Helm, PostgreSQL, Oracle SQL, RDS, Jira, Confluence, Amazon Bedrock, Bedrock AgentCore, AWS Networking, and Cloud Cost Optimization.

Key Responsibilities :

• AWS Cloud Infrastructure : Design, implement, and maintain AWS infrastructure with a focus on scalability, availability, security, reliability, and cost optimization.
• Microservices & Containerization : Manage and support distributed microservices architectures, including deployment, monitoring, troubleshooting, performance optimization, service meshes, and API gateways.
• Kubernetes Administration : Administer and optimize Kubernetes clusters, including Amazon EKS and self-managed environments, covering upgrades, networking, workload management, scaling, and resource optimization.
• Cloud Security & Compliance : Implement and manage AWS security services, including IAM, GuardDuty, Security Hub, WAF, KMS, Secrets Manager, AWS Config, and CloudTrail.
• DevSecOps Implementation : Integrate security testing, vulnerability scanning, container security, and compliance-as-code tools into CI/CD pipelines.
• CI/CD & Source Control : Manage Bitbucket repositories, branching strategies, permissions, and Bitbucket Pipelines. Build and optimize Jenkins pipelines using declarative and scripted approaches.
• Infrastructure as Code : Develop and maintain Terraform modules, manage remote state and workspaces, detect infrastructure drift, and implement reusable infrastructure provisioning practices.
• Database Administration : Provision, manage, secure, and optimize AWS RDS databases, particularly PostgreSQL and Oracle, including backups, replication, patching, performance tuning, and migrations.
• Jira & Confluence Administration : Manage projects, workflows, automation rules, permissions, user access, spaces, schemes, and plugins.
• Monitoring & Reliability : Define and monitor SLIs, SLOs, and SLAs; implement observability best practices; and participate in incident management, root cause analysis, and post-incident reviews.
• AI Agent Development : Design, build, and deploy AI agents using Amazon Bedrock and Bedrock AgentCore, including agent runtime, memory, tools, gateway integration, identity and access management, guardrails, and lifecycle management across environments.
• Cloud Connectivity : Support hybrid cloud connectivity using AWS Direct Connect, VPN, and Transit Gateway.
• Cost Optimization : Apply FinOps practices to monitor cloud expenditure, optimize resource utilization, and improve infrastructure efficiency.
• API Integrations : Integrate third-party APIs while implementing authentication, rate limiting, error handling, and webhook management.

Required Skills & Qualifications :

• 5+ years of hands-on experience with AWS cloud services, including EC2, ECS, EKS, Lambda, ALB, CDN, S3, CloudWatch, Amazon Bedrock, and Bedrock AgentCore.
• Strong understanding of AWS networking, multi-account strategies, landing zone architecture, and hybrid connectivity.
• 4+ years of practical experience with Terraform, including module development, remote state management, workspaces, drift detection, and state operations.
• Extensive experience administering Kubernetes, preferably Amazon EKS, including Helm, Kustomize, operators, RBAC, network policies, autoscaling, and multi-tenancy.
• Proven experience managing distributed microservices, service meshes, API gateways, and inter-service communication.
• Strong knowledge of AWS security services, including IAM, Service Control Policies (SCPs), WAF, KMS, Secrets Manager, AWS Config, and CloudTrail.
• Experience implementing least-privilege access, zero-trust principles, and cloud security compliance controls.
• Hands-on experience integrating DevSecOps tools such as Snyk, Trivy, Checkov, and SonarQube into CI/CD pipelines.
• Understanding of OWASP security principles, CIS benchmarks, vulnerability management, and container security.
• Proficiency in Bitbucket repository administration, branch permissions, and YAML-based Bitbucket Pipelines.
• Strong experience developing and maintaining Jenkins CI/CD pipelines, shared libraries, plugins, and build agents.
• Experience administering AWS RDS databases, particularly PostgreSQL and Oracle SQL, including backup, replication, performance tuning, and migration activities.
• Experience administering Jira and Confluence, including workflows, permissions, automation, and plugin management.
• Working knowledge of Azure services, particularly Web Apps and Logic Apps/Workflows.
• Practical experience with Amazon Bedrock, including model invocation, guardrails, and AI agent development and deployment using Bedrock AgentCore.
• Understanding of third-party API integration, authentication mechanisms, rate limiting, error handling, and webhook management.
• Familiarity with FinOps practices and cloud cost optimization.

Good-to-Have Skills :

• Additional Azure experience, including networking, Azure SQL Managed Instance, and Azure Kubernetes Service (AKS).
• Hands-on experience with AI-driven Development Lifecycle (AI-DLC) methodologies and tools such as Kiro.

Relevant certifications, such as :

• AWS Certified Solutions Architect
• AWS Certified DevOps Engineer – Professional
• AWS Machine Learning or Generative AI certifications
• Certified Kubernetes Administrator (CKA)
• HashiCorp Terraform certifications

Ideal Candidate Profile :

The ideal candidate is a hands-on cloud and DevSecOps professional who can manage enterprise-scale AWS infrastructure, automate deployments, strengthen security controls, troubleshoot complex distributed systems, and support AI agent development. Strong problem-solving skills, an automation-first mindset, and the ability to collaborate across development, security, and infrastructure teams are essential.

Role Overview: Take full ownership of infrastructure architecture, scaling, and uptime. Establish the technical roadmap, shape and formalize the SRE function, and coach engineers. Design, deploy, and run AI-scale infrastructure that enables real-time healthcare workflows.

Serve as a Founding Member, owning end-to-end infrastructure capabilities and introducing AI-first DevOps, SRE, and MLOps best practices, with direct collaboration alongside the Founder, Co-Founder, and Head of Engineering.

Key Responsibilities:

Architecture & Platform

• Design scalable, secure, cost-efficient AWS/GCP architectures for AI and healthcare workloads
• Lead IaC standards and reusable modules org-wide; own GitOps practices
• Architect optimized Kubernetes (EKS/GKE) for HA, scale, and GPU workload orchestration

Reliability Engineering

• Define and drive reliability targets (SLOs/SLIs); establish SRE practice
• Lead incident management, RCA, and blameless post-mortems for critical systems
• Partner on infrastructure hardening and compliance (SOC 2, HIPAA)

AI-First Engineering

• Lead AI/ML inference and GPU infrastructure scaling in production
• Evaluate and introduce AI tooling, platforms, and automation best practices
• Contribute to LLM deployment pipelines and AI systems reliability

Leadership & SDLC

• Mentor L1/L2 engineers; influence cross-team infrastructure decisions
• Drive DevSecOps maturity across the SDLC (policy-as-code, SBOM, supply-chain security)
• Evaluate and introduce new tooling and platforms

Key Requirements:

• 4–8 years infrastructure/platform/DevOps/SRE
• Deep expertise in AWS & GCP large-scale production systems
• Advanced Kubernetes (cluster design, multi-tenant ops, resource quotas)
• AI/ML inference or GPU infrastructure scaling (production track record)
• Strong Terraform / equiv. and GitOps practices
• Python, Go, or Bash scripting and automation
• Track record in scale, reliability, and cost efficiency
• Lead incident response and on-call practices

Nice-to-Have

• LLM Gateway architecture and optimization
• Zero-trust networking and advanced security/compliance (SOC 2, HIPAA)
• DevSecOps maturity: SBOM, supply-chain security, policy-as-code
• Open-source contributions or platform-team leadership

Why This Role?

• Build infrastructure and products powering real-world healthcare AI
• Work with AI-native engineering teams using cutting-edge tools (Claude Code, Cursor, Copilot)
• Mission-driven impact — improve patient outcomes and save thousands of staff hours
• High ownership, rapid learning, and significant career upside
• Global collaboration across India and the US
• Seed-stage growth — scale from Seed to Series A alongside the team
• Founding Member role and own the entire infrastructure capabilities, including bringing best AI-first practices in DevOps, SRE and MLOps; direct access to work with the Founder, Co-Founder and Head of Engineering

Job Description:

Pre-requisite skills required for a DevOps Engineer role include:

• 6+yrs exp in DevOps
• Experience working on Linux based infrastructure
• knowledge in AWS, docker, CI/CD tools
• Hands on exp in Python/shell scripting language
• hands on exp in AWS and Azure
• Work exp in Docker, Terraform, Ansible, Kubernetes, LINUX
• Excellent understanding of Ruby, Python, Perl, and Java
• Configuration and managing databases such as MySQL, Mongo
• Excellent troubleshooting
• Working knowledge of various tools, open-source technologies, and cloud services