DEVOPS/CLOUD OPS AWS

Job Summary:

We are seeking a highly skilled and proactive DevOps Engineer with 4+ years of experience to join our dynamic team. This role requires strong technical expertise across cloud infrastructure, CI/CD pipelines, container orchestration, and infrastructure as code (IaC). The ideal candidate should also have direct client-facing experience and a proactive approach to managing both internal and external stakeholders.

Key Responsibilities:

• Collaborate with cross-functional teams and external clients to understand infrastructure requirements and implement DevOps best practices.
• Design, build, and maintain scalable cloud infrastructure on AWS (EC2, S3, RDS, ECS, etc.).
• Develop and manage infrastructure using Terraform or CloudFormation.
• Manage and orchestrate containers using Docker and Kubernetes (EKS).
• Implement and maintain CI/CD pipelines using Jenkins or GitHub Actions.
• Write robust automation scripts using Python and Shell scripting.
• Monitor system performance and availability, and ensure high uptime and reliability.
• Execute and optimize SQL queries for MSSQL and PostgreSQL databases.
• Maintain clear documentation and provide technical support to stakeholders and clients.
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Required Skills:

• Minimum 4+ years of experience in a DevOps or related role.
• Proven experience in client-facing engagements and communication.
• Strong knowledge of AWS services – EC2, S3, RDS, ECS, etc.
• Proficiency in Infrastructure as Code using Terraform or CloudFormation.
• Hands-on experience with Docker and Kubernetes (EKS).
• Strong experience in setting up and maintaining CI/CD pipelines with Jenkins or GitHub.
• Solid understanding of SQL and working experience with MSSQL and PostgreSQL.
• Proficient in Python and Shell scripting.
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Preferred Qualifications:

AWS Certifications (e.g., AWS Certified DevOps Engineer) are a plus.

Experience working in Agile/Scrum environments.

Strong problem-solving and analytical skills.

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. 

Company - Apptware Solutions

Location Baner Pune

Team Size - 130+

Job Description -

Cloud Engineer with 8+yrs of experience

Roles and Responsibilities

● Have 8+ years of strong experience in deployment, management and maintenance of large systems on-premise or cloud

● Experience maintaining and deploying highly-available, fault-tolerant systems at scale

● A drive towards automating repetitive tasks (e.g. scripting via Bash, Python, Ruby, etc)

● Practical experience with Docker containerization and clustering (Kubernetes/ECS)

● Expertise with AWS (e.g. IAM, EC2, VPC, ELB, ALB, Autoscaling, Lambda, VPN)

● Version control system experience (e.g. Git)

● Experience implementing CI/CD (e.g. Jenkins, TravisCI, CodePipeline)

● Operational (e.g. HA/Backups) NoSQL experience (e.g. MongoDB, Redis) SQL experience (e.g. MySQL)

● Experience with configuration management tools (e.g. Ansible, Chef) ● Experience with infrastructure-as-code (e.g. Terraform, Cloudformation)

● Bachelor's or master’s degree in CS, or equivalent practical experience

● Effective communication skills

● Hands-on cloud providers like MS Azure and GC

● A sense of ownership and ability to operate independently

● Experience with Jira and one or more Agile SDLC methodologies

● Nice to Have:

○ Sensu and Graphite

○ Ruby or Java

○ Python or Groovy

○ Java Performance Analysis

Role: Cloud Engineer

Industry Type: IT-Software, Software Services

Functional Area: IT Software - Application Programming, Maintenance Employment Type: Full Time, Permanent

Role Category: Programming & Design

• Seeking an Individual carrying around 5+ yrs of experience.
• Must have skills - Jenkins, Groovy, Ansible, Shell Scripting, Python, Linux Admin
• Terraform, AWS deep knowledge to automate and provision EC2, EBS, SQL Server, cost optimization, CI/CD pipeline using Jenkins, Server less automation is plus.
• Excellent writing and communication skills in English. Enjoy writing crisp and understandable documentation
• Comfortable programming in one or more scripting languages
• Enjoys tinkering with tooling. Find easier ways to handle systems by doing some research. Strong awareness around build vs buy.

• Building and setting up new development tools and infrastructure
• Understanding the needs of stakeholders and conveying this to developers
• Working on ways to automate and improve development and release
  processes
• Testing and examining code written by others and analyzing results
• Ensuring that systems are safe and secure against cybersecurity
  threats
• Identifying technical problems and developing software updates and ‘fixes’
• Working with software developers and software engineers to ensure that development follows established processes and works as intended
• Planning out projects and being involved in project management decisions
  
  

• BE / MCA / B.Sc-IT / B.Tech in Computer Science or a related field.
• 4+ years of overall development experience.
• Strong understanding of cloud deployment and setup
• Hands-on experience with tools like Jenkins, Gradle etc.
• Deploy updates and fixes
• Provide Level 2 technical support
• Build tools to reduce occurrences of errors and improve customer experience
• Perform root cause analysis for production errors
• Investigate and resolve technical issues
• Develop scripts to automate deployment
• Design procedures for system troubleshooting and maintenance
• Skills and Qualifications
• Proficient with git and git workflows
• Working knowledge of databases and SQL
• Problem-solving attitude
• Collaborative team spirit

Srijan Technologies is hiring for the DevOps Lead position- Cloud Team with a permanent WFH option.

Immediate Joiners or candidates with 30 days notice period are preferred.

Requirements:-

• Minimum 4-6 Years experience in DevOps Release Engineering. 
• Expert-level knowledge of Git. 
• Must have great command over Kubernetes
• Certified Kubernetes Administrator
• Expert-level knowledge of Shell Scripting & Jenkins so as to maintain continuous integration/deployment infrastructure. 
• Expert level of knowledge in Docker. 
• Expert level of Knowledge in configuration management and provisioning toolchain; At least one of Ansible / Chef / Puppet. 
• Basic level of web development experience and setup: Apache, Nginx, MySQL 
• Basic level of familiarity with Agile/Scrum process and JIRA. 
• Expert level of Knowledge in AWS Cloud Services.