DevOps Engineer

Job Description

About the Open Position

Women join us as DevOps Engineer at Dailoqa, where you will be responsible for operationalizing cutting-edge machine learning and generative AI solutions, ensuring scalable, secure, and efficient deployment across infrastructure. You will work closely with data scientists, ML engineers, and business stakeholders to build and maintain robust MLOps pipelines, enabling rapid experimentation and reliable production implementation of AI models, including LLMs and real-time analytics systems.

To be successful as DevOps Engineer you should have experience with:

· Cloud sourcing, networks, VMs, performance, scaling, availability, storage, security, access management

· Deep expertise in one or more cloud platforms: AWS, Azure, GCP

· Strong experience in containerization and orchestration (Docker, Kubernetes, Helm)

· Familiarity with CI/CD tools: GitHub Actions, Jenkins, Azure DevOps, ArgoCD, etc.

· Proficiency in scripting languages (Python, Bash, PowerShell)

· Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML

· Strong understanding of DevOps principles applied to ML workflows.

Key Responsibilities may include:

· Design and implement scalable, cost-optimized, and secure infrastructure for AI-driven platforms.

· Implement infrastructure as code using tools like Terraform, ARM, or Cloud Formation.

· Automate infrastructure provisioning, CI/CD pipelines, and model deployment workflows.

· Ensure version control, repeatability, and compliance across all infrastructure components.

· Set up monitoring, logging, and alerting frameworks using tools like Prometheus, Grafana, ELK, or Azure Monitor.

· Optimize performance and resource utilization of AI workloads including GPU-based training/inference

· Experience with Snowflake, Databricks for collaborative ML development and scalable data processing.

· Understanding model interpretability, responsible AI, and governance.

· Contributions to open-source MLOps tools or communities.

· Strong leadership, communication, and cross-functional collaboration skills.

· Knowledge of data privacy, model governance, and regulatory compliance in AI systems.

· Exposure to LangChain, Vector DBs (e. g. , FAISS, Pinecone), and retrieval-augmented generation (RAG) pipelines.

Requirements
We’re seeking motivated and proactive professionals (8 – 10 years of experience) in Financial Services or Consulting, passionate about applying Agentic AI and first-principles thinking to transform Retail and Commercial Banking. Ideal candidates will have a solid background as a Business Analyst/Product owner, a strong understanding of banking products & processes, and a passion for delivering innovative solutions. Experience in Agentic AI is a plus, but not a must-have.