Sr. IT Engineer

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. 

DevOps Systems Engineer with experience in Docker Containers, Docker Swarm, Docker Compose, Ansible, Jenkins and other tools. As part of this role she/he must work with the container best practices in design, development and implementation.

At Least 4 Years of experience in DevOps with knowledge of:

• Docker
• Docker Cloud / Containerization
• DevOps Best Practices
• Distributed Applications
• Deployment Architecture
• Atleast AWS Experience
• Exposure to Kubernetes / Serverless Architecture

Skills:

• 3-7+ years of experience in DevOps Engineering
• Strong experience with Docker Containers, Implementing Docker Containers, Container Clustering
• Experience with Docker Swarm, Docker Compose, Docker Engine
• Experience with Provisioning and managing VM's - Virtual Machines
• Experience / strong knowledge with Network Topologies, Network Research,
• Jenkins, BitBucket, Jira
• Ansible or other Automation Configuration Management System tools
• Scripting & Programming using languages such as BASH, Perl, Python, AWK, SED, PHP, Shell
• Linux Systems Administration -: Redhat

Additional Preference:

Security, SSL configuration, Best Practices

About us:

HappyFox is a software-as-a-service (SaaS) support platform. We offer an enterprise-grade help desk ticketing system and intuitively designed live chat software.

We serve over 12,000 companies in 70+ countries. HappyFox is used by companies that span across education, media, e-commerce, retail, information technology, manufacturing, non-profit, government and many other verticals that have an internal or external support function.

To know more, Visit! - https://www.happyfox.com/

Responsibilities

• Build and scale production infrastructure in AWS for the HappyFox platform and its products.
• Research, Build/Implement systems, services and tooling to improve uptime, reliability and maintainability of our backend infrastructure. And to meet our internal SLOs and customer-facing SLAs.
• Implement consistent observability, deployment and IaC setups
• Lead incident management and actively respond to escalations/incidents in the production environment from customers and the support team.
• Hire/Mentor other Infrastructure engineers and review their work to continuously ship improvements to production infrastructure and its tooling.
• Build and manage development infrastructure, and CI/CD pipelines for our teams to ship & test code faster.
• Lead infrastructure security audits

Requirements

• At least 7 years of experience in handling/building Production environments in AWS.
• At least 3 years of programming experience in building API/backend services for customer-facing applications in production.
• Proficient in managing/patching servers with Unix-based operating systems like Ubuntu Linux.
• Proficient in writing automation scripts or building infrastructure tools using Python/Ruby/Bash/Golang
• Experience in deploying and managing production Python/NodeJS/Golang applications to AWS EC2, ECS or EKS.
• Experience in security hardening of infrastructure, systems and services.
• Proficient in containerised environments such as Docker, Docker Compose, Kubernetes
• Experience in setting up and managing test/staging environments, and CI/CD pipelines.
• Experience in IaC tools such as Terraform or AWS CDK
• Exposure/Experience in setting up or managing Cloudflare, Qualys and other related tools
• Passion for making systems reliable, maintainable, scalable and secure.
• Excellent verbal and written communication skills to address, escalate and express technical ideas clearly
• Bonus points – Hands-on experience with Nginx, Postgres, Postfix, Redis or Mongo systems.

Hands on Experience with Linux administration

Experience using Python or Shell scripting (for Automation) 

Hands-on experience with Implementation of CI/CD Processes 

Experience working  with one cloud platforms (AWS or Azure or Google) 

Experience working with configuration management tools such as Ansible & Chef 

Experience working with  Containerization tool Docker.

Experience working with Container Orchestration tool Kubernetes.

Experience in source Control Management including SVN and/or Bitbucket

& GitHub

Experience with setup & management of monitoring tools like Nagios, Sensu & Prometheus or any other popular tools 

Hands-on experience in Linux, Scripting Language & AWS is mandatory

Troubleshoot and Triage development, Production issues

Role : SRE

Experience : 4 - 8 Years

• Experience in building, deploying and operating cloud solutions on Kubernetes
• Strong expertise administrating and scaling Kubernetes on bare metal and CKA preferred
• Expertise on K8s Interfaces CNI, CSI, CRI and Service meshe
• Hands-on experience as a DevOps or Automation development
• Demonstrable knowledge of TCP/IP, Linux operating system internals, filesystems, disk/storage technologies and storage protocols.
• Experience working with Helm Charts and building out Infrastructure As Code (IaC)
• Experience in writing software to automate orchestration tasks at scale; we commonly use Python, Go, and Shell scripting
• Knowledge of systems (Linux, GNU tooling), networking (OSI model, DNS, routing) and virtualization vs containerization
• Expertise in CI/CD tooling for cloud-based applications specifically Terraform / CloudFormation, Jenkins and Git
• Architected CNF Orchestration with Kubernetes
• Strong understanding of the principles of 12-factor apps and modern containerized microservices
• Plan for reliability by designing systems to work across our multi-region and multi-cloud environments
• Experience developing and using Application & Integration stacks/tools such as Kafka, Spring Cloud, Apache Camel, Kubernetes, Docker, Redis, Knative, and NoSQL

Job Description:

Mandatory Skills:

Should have strong working experience with Cloud technologies like AWS and Azure.

Should have strong working experience with CI/CD tools like Jenkins and Rundeck.

Must have experience with configuration management tools like Ansible.

Must have working knowledge on tools like Terraform.

Must be good at Scripting Languages like shell scripting and python.

Should be expertise in DevOps practices and should have demonstrated the ability to apply that knowledge across diverse projects and teams.

Preferable skills:

Experience with tools like Docker, Kubernetes, Puppet, JIRA, gitlab and Jfrog.

Experience in scripting languages like groovy.

Experience with GCP

Summary & Responsibilities:

 Write build pipelines and IaaC (ARM templates, terraform or cloud formation).

 Develop ansible playbooks to install and configure various products.

 Implement Jenkins and Rundeck jobs( and pipelines).

 Must be a self-starter and be able to work well in a fast paced, dynamic environment

 Work independently and resolve issues with minimal supervision.

 Strong desire to learn new technologies and techniques

 Strong communication (written / verbal ) skills

Qualification:

Bachelor's degree in Computer Science or equivalent.

4+ years of experience in DevOps and AWS.

2+ years of experience in Python, Shell scripting and Azure.