Senior Azure Data / MLOps / AI Platform Engineer at NeoGenCode Technologies Pvt Ltd · Remote only · 5 - 8 years · ₹8L - ₹15L / yr · Raised funding · Remote only · Posted 7 Jul 2026

Senior Azure Data / MLOps / AI Platform Engineer
Job Title : Senior Azure Data / MLOps / AI Platform Engineer
Experience : 6+ Years
Employment Type : Contract
Role Level : Senior
Project : Leading South Africa Telecommunications Operator
Department : Data & AI Engineering
Job Overview :
We are looking for a Senior Azure Data / MLOps / AI Platform Engineer to design, build, and manage Azure-native cloud infrastructure, MLOps pipelines, and AI platforms supporting enterprise-scale data products and AI applications.
The ideal candidate will have strong expertise in Azure Cloud, Azure Databricks, Infrastructure as Code, CI/CD, Kubernetes, and MLOps, enabling scalable deployment of machine learning, GenAI, and AI Agent solutions.
Mandatory Skills :
Microsoft Azure, Azure Databricks, Terraform/Bicep, Azure DevOps or GitHub Actions, Docker, Kubernetes (AKS), MLflow, Azure ML, Kubeflow, CI/CD, MLOps, Infrastructure as Code, Azure Monitor, Prometheus, Grafana, Vector Databases, AI Platform Engineering.
Key Responsibilities :
- Design, deploy, and maintain Azure cloud infrastructure, landing zones, networking, storage, and compute environments.
- Build and manage Azure Databricks environments for data engineering and AI workloads.
- Develop Infrastructure as Code using Terraform or Bicep.
- Create and maintain CI/CD pipelines using Azure DevOps or GitHub Actions.
- Implement MLOps solutions including model deployment, MLflow, model registry, monitoring, drift detection, and automated retraining.
- Deploy and manage AI platform components such as vector databases, model-serving endpoints, and AI infrastructure.
- Manage containerized workloads using Docker, Kubernetes (AKS), and cloud-native deployment practices.
- Monitor platform performance, observability, security, reliability, and infrastructure costs.
- Collaborate with Data Engineering, AI/ML, GenAI, Cybersecurity, and Solution Architecture teams to deliver scalable enterprise AI platforms.
Required Skills :
- 6+ years of experience in Cloud, Platform, or MLOps Engineering.
- Strong hands-on experience with Microsoft Azure services and Azure infrastructure.
- Expertise in Azure Databricks, Terraform/Bicep, and Infrastructure as Code.
- Experience with Azure DevOps or GitHub Actions for CI/CD.
- Strong MLOps knowledge including MLflow, Azure ML, Kubeflow, Model Registry, Model Deployment, Monitoring, and Drift Detection.
- Experience with Docker, Kubernetes (AKS), and Container Orchestration.
- Familiarity with Vector Databases, GenAI infrastructure, LLM deployment, and AI platform engineering.
- Experience with monitoring tools such as Azure Monitor, Prometheus, and Grafana.
Good to Have :
- Experience with Azure OpenAI, AI platforms, or enterprise GenAI deployments.
- Telecom, Banking, or other large enterprise domain experience.
- Microsoft Azure, Databricks, or MLOps certifications.

About NeoGenCode Technologies Pvt Ltd
About
Welcome to Neogencode Technologies, an IT services and consulting firm that provides innovative solutions to help businesses achieve their goals. Our team of experienced professionals is committed to providing tailored services to meet the specific needs of each client. Our comprehensive range of services includes software development, web design and development, mobile app development, cloud computing, cybersecurity, digital marketing, and skilled resource acquisition. We specialize in helping our clients find the right skilled resources to meet their unique business needs. At Neogencode Technologies, we prioritize communication and collaboration with our clients, striving to understand their unique challenges and provide customized solutions that exceed their expectations. We value long-term partnerships with our clients and are committed to delivering exceptional service at every stage of the engagement. Whether you are a small business looking to improve your processes or a large enterprise seeking to stay ahead of the competition, Neogencode Technologies has the expertise and experience to help you succeed. Contact us today to learn more about how we can support your business growth and provide skilled resources to meet your business needs.
Candid answers by the company
IT & Engineering Talent Staffing
- Provides full-time and contract-based hiring, delivering handpicked, pre‑screened developers across tech stacks—ranging from web, mobile, AI/ML, Web3/blockchain.
- Maintains a bench o vetted candidates, offering fast delivery of interview-ready profiles—often within 24 hours.
- Offers payroll management, handling compliance, tax, attendance, and documentation for both contractors and full-time employees.
2. End-to-End Project Delivery
- Delivers full-stack development solutions: web, mobile, cloud, AI/ML, Blockchain/Web3.
- Manages entire project lifecycle—requirements gathering, design (UI/UX), development, deployment, and ongoing support .
3. Additional Offerings
- Expands into cybersecurity consulting, digital marketing, and cloud platform services (like AWS, GCP, Azure) .
- Provides strategic IT consulting to align technology solutions with business objectives
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- 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
- 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
🚀 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
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
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.
Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.
You Will:
- Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
- Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
- CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
- Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
- Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
- Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
- Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
- Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
- Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
- Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
- Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
- Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
- Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
- Perform other duties as assigned
You Have:
- Enterprise SaaS software solutions with high availability and scalability
- Solution handling large scale structured and unstructured data from varied data sources
- Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
- Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
- In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
- AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
- Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
- Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
- Programming languages like Python and SQL
- Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
- Solution Cost Optimisations and design to cost
- Legally eligible to work in India on an ongoing basis
Get to Know Us:
At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.
Equal Opportunity Employer:
Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, India, and Singapore. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.
Job application link : https://grnh.se/z7qx2ehx1us
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
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
Position Overview
The AI Observability Engineer will be instrumental in implementation of scalable, cloud-native solutions to meet the growing needs of our Data & Development team. The successful candidate will demonstrate the ability to abstract complexity and create reusable, scalable patterns that accelerate development. The AI Observability Engineer will build and maintain a robust framework to ensure the reliability and maintainability of DPR Construction's complex AI systems.
Responsibilities
- Standardize observability practices across AI/ML and other development teams including logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms
- Lead hands-on implementation of automation-first DevOps and MLOps practices, enabling infrastructure-as-code and consistent, repeatable environment provisioning
- Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly detection
- Deploy, maintain and monitor containerized ML workloads
- Extend existing CI/CD pipelines to support automated infrastructure changes and ML workflows
- Implement AI-driven data validation, schema and concept drift detection and metadata management.
- Establish governance frameworks for AI systems, including bias detection, explainability, and auditability
- Extend existing Azure RBAC strategy by automating role and permission management to reduce manual intervention
- Develop automated test suites for model performance, regression, edge cases and bias validation
- Monitor model KPIs (accuracy, precision, recall, latency, calibration)
- Ensure reproducability of experiments and production models
- Act as a technical point of contact for DevOps and MLOps practices, developing reusable patterns, documentation, and proof-of-concepts to drive adoption
Qualifications
- Bachelor’s degree in computer science, Data Science, Information Systems, or a related field
- 5+ 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
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Azure DevOps Engineer
Experience
5-10 years of hands-on experience in Platform Engineering, Cloud Engineering, SRE, DevOps or Infrastructure Engineering roles.
Priority 1 – Must Have (Hands-On)
Azure Cloud Platform
· Strong hands-on experience supporting Azure workloads in production environments.
· Experience designing, building and supporting Azure infrastructure using Terraform.
· Good understanding of Azure networking and connectivity patterns.
· Experience supporting:
Ø AKS
Ø Application Gateway
Ø Azure Traffic Manager
Ø Key Vault
Ø Azure Monitor / Log Analytics
Ø Managed Identities
Ø Service Principals
Ø Private Endpoints
Ø VNets, NSGs and Route Tables
Kubernetes / AKS
- Strong practical experience operating and supporting AKS.
- Ability to troubleshoot:
Ø Pod failures
Ø Ingress issues
Ø DNS issues
Ø SSL/TLS certificate issues
Ø Network routing issues
Ø Performance and availability incidents
- Experience with:
Ø Helm
Ø Ingress Controllers
Ø Cluster upgrades
Ø Scaling
Ø Monitoring
Terraform
· Strong hands-on experience writing and maintaining Terraform.
· Experience creating reusable modules.
· Experience managing:
· State files
· Remote backends
· Environment promotion
· Infrastructure lifecycle
Linux & Scripting
· Strong Linux administration fundamentals.
· Practical experience troubleshooting production issues.
· Bash scripting mandatory.
· Python desirable.
Application Support / Troubleshooting
Must be comfortable supporting business applications end-to-end.
Priority 2 – Highly Desirable
GitHub & DevOps Platform
Hands-on experience with:
· GitHub Enterprise
· GitHub Actions
· Shared workflows
· Reusable pipelines
· Repository onboarding
· Branch protections
· GitHub security features
Experience supporting:
· Runner issues
· Disk space issues
· Network connectivity issues
· Dependency failures
· Self-hosted runners lifecycle management
API Management
Pipeline failures
GitOps
Experience with:
· ArgoCD
· GitOps deployment models
· Kubernetes deployment automation
Monitoring & Observability
Experience working with:
· Prometheus
· Grafana
· Azure Monitor
· Log Analytics
· Application Insights
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










