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Data & AI Engineer - Cyber Risk Intelligence Platform - India/Remote at Quantara AI. Location Information: Anywhere in the World. . Headquarters:. Not Specified . . Data & AI Engineer - Cyber Risk Intelligence Platform - India. Location:. India (Remote). About Quantara AI & the Role. Quantara AI is a next-generation . Cyber Risk Intelligence and Governance. platform that helps CISOs, Boards, and executive teams . quantify, prioritize, and communicate cyber risk in business terms. . Our AI-powered solution combines . Cyber Risk Quantification (CRQ). and . Continuous Threat Exposure Management (CTEM). to automate compliance, identify the top 1% of exposures that truly matter, and deliver insights that drive measurable business resilience.. We are seeking a highly skilled . Data & AI Engineer. to help design and scale the data and AI backbone of our platform. This role involves developing . large-scale data pipelines. , building . AI/LLM-powered systems. , and implementing . enterprise-grade backend and orchestration architectures. that support data-driven decision-making.. You will work on end-to-end . data and AI infrastructure. , including . ETL/ELT development, LLM orchestration, API engineering, and metric computation. -helping evolve a scalable, secure, and intelligent enterprise platform.. Key Responsibilities. 1. Data Engineering & Architecture. Design, build, and maintain . enterprise-scale data pipelines. for structured, semi-structured, and unstructured data.. Develop . data acquisition and transformation workflows. integrating multiple APIs and business data sources.. Create and optimize . relational and analytical data models. for performance, scalability, and reliability.. Establish . data quality, validation, and governance standards. across ingestion and analytics workflows.. Enable . real-time and batch processing pipelines. supporting large-scale enterprise applications.. 2. AI/LLM Development & Orchestration. Design, develop, and deploy . LLM-driven and agentic AI applications. for analytics, automation, and reasoning.. Build . Retrieval-Augmented Generation (RAG). pipelines and knowledge orchestration layers across enterprise data.. Fine-tune and train . language models. using modern open-source frameworks and libraries.. Implement . NLP and conversational AI components. , including chatbots, summarization, and question-answering systems.. Optimize . model orchestration, embeddings, and context management. for scalable AI inference.. 3. Backend Development & API Engineering. Develop and manage . RESTful APIs and backend services. to support AI, analytics, and data operations.. Implement . secure API access controls. , error handling, and logging.. Build . microservices and event-driven architectures. to deliver modular, reliable data and AI capabilities.. Integrate backend components with data pipelines, analytics engines, and external systems.. 4. Metrics Computation & Quantification. Design automated engines for computing . risk, ROI, RRI, maturity, and performance metrics. .. Integrate quantification logic into business and risk data models to provide real-time visibility.. Develop scalable . data and AI computation frameworks. that support executive reporting and analytics.. Collaborate with product and data teams to ensure metric accuracy, transparency, and explainability.. 5. CI/CD, Deployment & Cloud Operations. Implement and manage . CI/CD pipelines. for testing, deployment, and environment management.. Work with . cloud-native technologies. for infrastructure automation, monitoring, and scaling.. Use . containerization and orchestration tools. for consistent, portable, and secure deployment.. Establish performance monitoring, observability, and alerting across production systems.. Qualifications. 6-10 years. of experience in . data engineering, backend development, or AI platform engineering. .. Proven success in . product development environments. and experience building . enterprise-grade SaaS applications. .. Strong programming proficiency in . Python. or equivalent languages for backend and data systems.. Deep understanding of . SQL. and relational databases, including schema design and performance tuning.. Experience building . ETL/ELT pipelines. , API integrations, and data orchestration workflows.. Hands-on experience with . AI and LLM technologies. (e.g., Transformers, RAG, embeddings, vector databases).. Familiarity with . MLOps and LLMOps concepts. , including model deployment, scaling, and monitoring.. Practical experience with technologies such as:. Data frameworks: Airflow, dbt, Spark, Pandas, Kafka, Kinesis. Cloud & DevOps: AWS, GCP, Azure, Terraform, Docker, Kubernetes. Databases: PostgreSQL, MySQL, Snowflake, BigQuery, DynamoDB. AI/LLM: LangChain, Hugging Face, OpenAI API, LlamaIndex, Weaviate, Pinecone, FAISS. CI/CD: Jenkins, GitHub Actions, GitLab CI, or similar tools. Strong knowledge of . data security, scalability, and performance optimization. in production systems.. Preferred Skills. Background in . cybersecurity, risk analytics. , or . financial data systems. is a plus.. Experience with . agentic AI systems. , . autonomous orchestration. , or . conversational analytics. .. Understanding of . data governance, metadata management. , and . compliance automation. .. Exposure to . streaming data systems. and . real-time analytics architectures. .. Ability to . mentor junior engineers. and contribute to design and architectural discussions.. Compensation. Competitive India market base salary + performance-based incentives.. Open to . Contract-to-Hire (CTH). with potential for full-time conversion based on performance.. . To apply:. . https://weworkremotely.com/remote-jobs/quantara-ai-data-ai-engineer-cyber-risk-intelligence-platform-india-remote.