Senior Technical Lead - DevOps

Role & Responsibilities

We are looking for a hands-on AWS Cloud Engineer to support day-to-day cloud operations, automation, and reliability of AWS environments. This role works closely with the Cloud Operations Lead, DevOps, Security, and Application teams to ensure stable, secure, and cost-effective cloud platforms.

Key Responsibilities-

• Operate and support AWS production environments across multiple accounts
• Manage infrastructure using Terraform and support CI/CD pipelines
• Support Amazon EKS clusters, upgrades, scaling, and troubleshooting
• Build and manage Docker images and push to Amazon ECR
• Monitor systems using CloudWatch and third-party tools; respond to incidents
• Support AWS networking (VPCs, NAT, Transit Gateway, VPN/DX)
• Assist with cost optimization, tagging, and governance standards
• Automate operational tasks using Python, Lambda, and Systems Manager

Ideal Candidate

• Strong hands-on AWS experience (EC2, VPC, IAM, S3, ALB, CloudWatch)
• Experience with Terraform and Git-based workflows
• Hands-on experience with Kubernetes / EKS
• Experience with CI/CD tools (GitHub Actions, Jenkins, etc.)
• Scripting experience in **Python or Bash**
• Understanding of monitoring, incident management, and cloud security basics

Nice to Have-

• AWS Associate-level certifications
• Experience with Karpenter, Prometheus, New Relic
• Exposure to FinOps and cost optimization practices

We are seeking an experienced MLOps Architect who can drive end-to-end implementation of the proposal being prepared for the initiative and also contribute broadly across other enterprise AI/ML programs. This role demands a strong architectural mindset, hands-on technical depth, and the ability to design scalable, cloud-native machine learning operations across traditional ML and modern LLM workflows.

The ideal candidate will bring experience with SageMaker-based MLOps pipelines, evaluation of equivalent tooling stacks, hybrid MLOps/LLMOps automation, CI/CD orchestration, governance, and production-grade scalability patterns.

Must have skills & Qualifications:

• 8+ years working in ML/AI engineering or MLOps roles with strong architecture exposure.
• Strong expertise in AWS cloud-native ML stack, including: SageMaker(primary), ECS, Lambda, API Gateway, CI/CD (CodeBuild/CodePipeline or equivalent)
• Hands-on experience with at least one major MLOps toolset and awareness of alternatives: MLflow, Kubeflow, SageMaker Pipelines, Airflow, BentoML, KServe, Seldon.
• Deep understanding of model lifecycle management (feature engineering->training -> registry -> deployment -> monitoring).
• Experience implementing or supporting LLMOps pipelines, including: prompt versioning, evaluation metrics, automation frameworks.
• Deep understanding of ML lifecycle: data ingestion, feature engineering, training, evaluation, model packaging, CI/CD, drift detection, monitoring, and governance.
• Strong experience with AWS SageMaker (Pipelines, Feature Store, Model Registry, Model Monitor).
• Experience implementing ML CI/CD pipelines including automated training, testing, validation, model promotion, and endpoint deployment.
• Strong SQL and data transformation experience using Snowflake, Databricks, Spark.
• Experience with feature engineering pipelines and Feature Store management.
• Understanding of lineage tracking: training data snapshot, feature versions, code versioning, metadata tracking, reproducibility.
• Hands-on experience with Bedrock, OpenAI, Anthropic, or Llama models.
• Experience with CloudWatch, SageMaker Model Monitor, Prometheus/Grafana.
• Strong foundation in Python and cloud-native development patterns.
• Solid understanding of security best practices, IAM, secrets management, and artifact governance.

Good to have skills:

• Experience with vector databases, RAG pipelines, or multi-agent AI systems.
• Exposure to DevOps and infrastructure-as-code (Terraform, Helm, CDK).
• Hands-on understanding of model drift detection, A/B testing, canary rollouts, and blue-green deployments.
• Familiarity with Observability stacks (Prometheus, Grafana, CloudWatch, OpenTelemetry).
• Knowledge of Lakehouse (Delta/Iceberg/Hudi) architecture.
• Ability to translate business goals into scalable AI/ML platform designs.
• Strong communication and cross-team collaboration skills.
• Ability to guide engineering teams through technical uncertainty and design choices.

Key Responsibilities:

• Architect and implement the MLOps strategy for the programme, ensuring alignment with the project proposal and delivery roadmap.
• Design and own enterprise-grade ML/LLM pipelines covering model training, validation, deployment, versioning, monitoring, and CI/CD automation.
• Build container-oriented ML platforms (EKS-first) while evaluating alternative orchestration tools with similar capabilities (Kubeflow, SageMaker, MLflow, Airflow, etc.).
• Implement hybrid MLOps + LLMOps workflows, including prompt/version governance, evaluation frameworks, and monitoring for LLM-based systems.
• Serve as a technical authority across multiple internal and customer projects, contributing architectural patterns, best practices, and reusable frameworks.
• Enable observability, monitoring, drift detection, lineage tracking, and auditability across ML/LLM systems.
• Collaborate with cross-functional teams — data engineering, platform, DevOps, and client stakeholders — to deliver production-ready ML solutions.
• Ensure all solutions adhere to security, governance, and compliance expectations, particularly around handling cloud services, Kubernetes workloads, and MLOps tools.
• Conduct architecture reviews, troubleshoot complex ML system issues, and guide teams through implementation across cloud-native ML platforms.
• Mentor engineers and provide guidance on modern MLOps tools, platform capabilities, and best practices. 

Key Skills Required:

·         You will be part of the DevOps engineering team, configuring project environments, troubleshooting integration issues in different systems also be involved in building new features for next generation of cloud recovery services and managed services. 

·         You will directly guide the technical strategy for our clients and build out a new capability within the company for DevOps to improve our business relevance for customers. 

·         You will be coordinating with Cloud and Data team for their requirements and verify the configurations required for each production server and come with Scalable solutions.

·         You will be responsible to review infrastructure and configuration of micro services and packaging and deployment of application

To be the right fit, you'll need:

·         Expert in Cloud Services like AWS.

·         Experience in Terraform Scripting.

·         Experience in container technology like Docker and orchestration like Kubernetes.

·         Good knowledge of frameworks such as Jenkins, CI/CD pipeline, Bamboo Etc.

·         Experience with various version control system like GIT, build tools (Mavan, ANT, Gradle ) and cloud automation tools (Chef, Puppet, Ansible)

Key Responsibilities:

• ☁️ Manage cloud infrastructure and automation on AWS, Google Cloud (GCP), and Azure.
• 🖥️ Deploy and maintain Windows Server environments, including Internet Information Services (IIS).
• 🐧 Administer Linux servers and ensure their security and performance.
• 🚀 Deploy .NET applications (ASP.Net, MVC, Web API, WCF, etc.) using Jenkins CI/CD pipelines.
• 🔗 Manage source code repositories using GitLab or GitHub.
• 📊 Monitor and troubleshoot cloud and on-premises server performance and availability.
• 🤝 Collaborate with development teams to support application deployments and maintenance.
• 🔒 Implement security best practices across cloud and server environments.

Required Skills:

• ☁️ Hands-on experience with AWS, Google Cloud (GCP), and Azure cloud services.
• 🖥️ Strong understanding of Windows Server administration and IIS.
• 🐧 Proficiency in Linux server management.
• 🚀 Experience in deploying .NET applications and working with Jenkins for CI/CD automation.
• 🔗 Knowledge of version control systems such as GitLab or GitHub.
• 🛠️ Good troubleshooting skills and ability to resolve system issues efficiently.
• 📝 Strong documentation and communication skills.

Preferred Skills:

• 🖥️ Experience with scripting languages (PowerShell, Bash, or Python) for automation.
• 📦 Knowledge of containerization technologies (Docker, Kubernetes) is a plus.
• 🔒 Understanding of networking concepts, firewalls, and security best practices.

Primary Skills:

Linux – Ubuntu Administration, Git, Gerrit, Jenkins Administration, Cloud services (Preferred AWS) Apache, Ansible, Python, Postgresql, Rabbit MQ, CloudWatch AWS, CFT in AWS

Additional Skills Required:

• Should have experience working with Jenkins, Git, Gerrit
• Should have Good understanding of AWS Security and execution.
• Should have Good python skills
• Should have experience of working with GIT, Gerrit, Jira, Confluence,
• Exposure to messaging systems Rabbit MQ
• Exposure to Html, Groovy, Javascript, shell scripting
• Exposure to Kibana, Provisioning, capacity planning and performance analysis at various levels
• Exposure to Android skills.
• Should have experience in working with cloud-native architecture.
• Experience with log stash and elastic search
• Expert in Full Stack design technique as well as experience working across large environments with multiple operating systems/infrastructure for large-scale programs
• May be recognized as a leader in Agile and cultivating teams working in Agile frameworks
• Strong understanding of techniques such as Continuous Integration, Continuous Delivery, Test Driven Development, Cloud Development, resiliency, security
• Stays abreast of cutting edge technologies/trends and uses experience to influence application of those technologies/trends to support the business
• Experience on Modelling and Provisioning cloud infrastructure using AWS CloudFormation

Key Responsibilities:

• Perform a Technical Lead role for DevOPs development and support teams.
• Need to communicate & coordinate with both offshore and onsite teams
• Should translate business requirements into project plans and workable item/activities
• Have a thorough understanding of software development lifecycle and the ability to implement software following the structured approach.
• Need to perform in-depth technical reviews of project deliverables and ensure it should be defect free (minimize post release defects).
• Understand the current applications and technical architecture and improvise them as needed.
• Stay abreast of new technologies, methods to optimize development process and latest SDKs, testing tools etc

PRAXINFO Hiring DevOps Engineer.

Position : DevOps Engineer

Job Location : C.G.Road, Ahmedabad

EXP : 1-3 Years

Salary : 40K - 50K

Required skills:

⦿ Good understanding of cloud infrastructure (AWS, GCP etc)

⦿ Hands on with Docker, Kubernetes or ECS

⦿ Ideally strong Linux background (RHCSA , RHCE)

⦿ Good understanding of monitoring systems (Nagios etc), Logging solutions (Elastisearch etc)

⦿ Microservice architectures

⦿ Experience with distributed systems and highly scalable systems

⦿ Demonstrated history in automating operations processes via services and tools ( Puppet, Ansible etc)

⦿ Systematic problem-solving approach coupled with a strong sense of ownership and drive.

If anyone is interested than share your resume at hiring at praxinfo dot com!

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