"Cipher" - Derived from the word Sifr meaning 0 or nothing. "Ops" - Operations At CipherOps, we are building an agentic-first, cursor-style AI platform that streamlines your entire DevOps lifecycle. From provisioning infrastructure as code and managing GitOps deployments, running observability queries, and enforcing security and compliance checks to Incident Management, CoOps unifies your cloud, CI/CD, monitoring, and SRE into a single, intuitive platform with agent chat interface. Mission Empower DevOps teams to accelerate delivery and reduce risk by automating repetitive tasks, surfacing real-time insights, and preserving institutional knowledge - all through a conversational interface that grows with your organization. Vision Become the indispensable AI DevOps assistant for every engineering team - eliminating manual toil, breaking down silos between DevOps and SRE, and providing a unified "single pane of glass" for infrastructure, deployments, incidents, and security so businesses can innovate without limits. Qualifications Front-End Development and Responsive Web Design skills Internship Experience in web development & React Understanding of Software Development principles Strong problem-solving and analytical skills Ability to work well in a team environment Bachelor's degree in Computer Science or relevant field Brownie Points Exposure to Typescript Knowledge of Redux/Redux Toolkit

As our AI Engineer, you’ll own the design, development, and production-grade deployment of our machine learning and NLP pipelines. You’ll work cross-functionally with backend (Java/Spring Boot), data (Kafka/MongoDB/ES), and frontend (React) teams to embed AI capabilities throughout. Responsibilities Build & Deploy ML/NLP Models Design end-to-end ML pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation and monitoring. Train, deploy and operate predictive models (classification, regression, anomaly detection) to drive actionable insights across all MCP sources. Implement NLP components - such as text classification, summarization, and conversational interfaces—to enhance chat-driven workflows and knowledge retrieval. Data Engineering & Integration Ingest, clean, and normalize data from Kafka/Mongo and third-party APIs Define and maintain JSON-schema validations and transformation logic Collaborate with backend services to embed AI outputs Platform & Service Collaboration Work with Java/Spring Boot teams to wrap models as REST endpoints or Kafka stream processors Ensure end-to-end monitoring, logging, and performance tuning within Kubernetes Partner with frontend engineers to surface AI insights in React-based chat interfaces Continuous Improvement Establish A/B testing, metrics, and feedback loops to tune model accuracy and latency Stay on top of LLM and MLops best practices to evolve our AI stack Qualifications Experience: 2–3 years in ML/AI or data science roles, preferably in SaaS. Languages & Frameworks: Python and Familiarity with Java & Spring Boot for service integrations. Data & Infrastructure: Hands-on with Kafka, MongoDB, Redis or similar. Experience containerizing in Docker and deploying on Kubernetes. JSON-path/JSONLogic or similar transformation engines. Soft Skills: Excellent communication - able to translate complex AI concepts to product and customer teams. Nice-to-Haves Experience integrating LLMs or building vector search indexes for semantic retrieval Prior work on chatbots or conversational UIs Familiarity with DevOps stack. (AWS/Azure, k8s, GitOps, Security, Observability and Incident management)