
- Candidate should be able to write the sample programs using the Tools (Bash, PowerShell, Python or Shell scripting)
- Analytical/logical reasoning
- GitHub Actions
- Should have good working experience with GitHub Actions
- Repository/Workflow Dispatch, writing reusable workflows, etc
- AZ CLI commands
- Hands-on experience with AZ CLI commands

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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 Qualifications :
- At least 2 years of hands-on experience with cloud infrastructure on AWS or GCP
- Exposure to configuration management and orchestration tools at scale (e.g. Terraform, Ansible, Packer)
- Knowledge in DevOps tools (e.g. Jenkins, Groovy, and Gradle)
- Familiarity with monitoring and alerting tools(e.g. CloudWatch, ELK stack, Prometheus)
- Proven ability to work independently or as an integral member of a team
Preferable Skills :
- Familiarity with standard IT security practices such as encryption, credentials and key management
- Proven ability to acquire various coding languages (Java, Python- ) to support DevOps operation and cloud transformation
- Familiarity in web standards (e.g. REST APIs, web security mechanisms)
- Multi-cloud management experience with GCP / Azure
- Experience in performance tuning, services outage management and troubleshooting
Bachelor's degree in Computer Science or a related field, or equivalent work experience
Strong understanding of cloud infrastructure and services, such as AWS, Azure, or Google Cloud Platform
Experience with infrastructure as code tools such as Terraform or CloudFormation
Proficiency in scripting languages such as Python, Bash, or PowerShell
Familiarity with DevOps methodologies and tools such as Git, Jenkins, or Ansible
Strong problem-solving and analytical skills
Excellent communication and collaboration skills
Ability to work independently and as part of a team
Willingness to learn new technologies and tools as required
JOB DETAILS
What You'll Do
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.
Skills:
- Strong working knowledge of AWS.
- Implements AWS cloud platform.
- Infrastructure as Code, GitLab CI/CD, and DevOps standard methodologies
- scripting in Shell, Python, Ruby or any preferred scripting language
Terraform expertise is a MUST for this role.
a short exercise on terraform to all shortlisted candidates to demonstrate their hands-on skills on terraform before rolling out the offer
Desired Profile
Providing expertise on all matters related to CI, CD and DevOps.
Building and maintaining highly available production systems.
Developing and maintaining release related documents, such as release plan, release notes etc.
Ensuring quality releases and managing release and configuration change conflicts to resolution.
Tracking release and publishing release notes. Investigating and resolving technical issues by deploying updates/ fixes.
Onboard applications to DevOps process.
Setup and configure build jobs.
Create automated deployment scripts.
Configure JIRA workflow, and integrate with Jenkins / Micro-services.
Qualification
Degree/Diploma in Computer Science, Engineering or related field and have previous experience as a DevOps Engineer.
AWS Certification will be a plus.
Experience of automation and provisioning approaches, using tools such as Terraform & Cloud Formation
Skillset Required
Solid experience within release management, infra architecture, CI&CD.
Highly goal driven and work well in fast paced environments.
Proven experience of using Jenkins, Unix Shell Commands, Container technology (Docker, Kubernetes),
Java Programming, Groovy Script, Git, Code Branching Strategy, Maven, Gradle, JIRA, ECS, OpenShift.
What you do :
- Developing automation for the various deployments core to our business
- Documenting run books for various processes / improving knowledge bases
- Identifying technical issues, communicating and recommending solutions
- Miscellaneous support (user account, VPN, network, etc)
- Develop continuous integration / deployment strategies
- Production systems deployment/monitoring/optimization
-
Management of staging/development environments
What you know :
- Ability to work with a wide variety of open source technologies and tools
- Ability to code/script (Python, Ruby, Bash)
- Experience with systems and IT operations
- Comfortable with frequent incremental code testing and deployment
- Strong grasp of automation tools (Chef, Packer, Ansible, or others)
- Experience with cloud infrastructure and bare-metal systems
- Experience optimizing infrastructure for high availability and low latencies
- Experience with instrumenting systems for monitoring and reporting purposes
- Well versed in software configuration management systems (git, others)
- Experience with cloud providers (AWS or other) and tailoring apps for cloud deployment
-
Data management skills
Education :
- Degree in Computer Engineering or Computer Science
- 1-3 years of equivalent experience in DevOps roles.
- Work conducted is focused on business outcomes
- Can work in an environment with a high level of autonomy (at the individual and team level)
-
Comfortable working in an open, collaborative environment, reaching across functional.
Our Offering :
- True start-up experience - no bureaucracy and a ton of tough decisions that have a real impact on the business from day one.
-
The camaraderie of an amazingly talented team that is working tirelessly to build a great OS for India and surrounding markets.
Perks :
- Awesome benefits, social gatherings, etc.
- Work with intelligent, fun and interesting people in a dynamic start-up environment.
- Strong Understanding of Linux administration
- Good understanding of using Python or Shell scripting (Automation mindset is key in this role)
- Hands on experience with Implementation of CI/CD Processes
Experience working with one of these cloud platforms (AWS, Azure or Google Cloud) - Experience working with configuration management tools such as Ansible, Chef
Experience in Source Control Management including SVN, Bitbucket and GitHub
Experience with setup & management of monitoring tools like Nagios, Sensu & Prometheus
Troubleshoot and triage development and Production issues - Understanding of micro-services is a plus
Roles & Responsibilities
- Implementation and troubleshooting on Linux technologies related to OS, Virtualization, server and storage, backup, scripting / automation, Performance fine tuning
- LAMP stack skills
- Monitoring tools deployment / management (Nagios, New Relic, Zabbix, etc)
- Infra provisioning using Infra as code mindset
- CI/CD automation










