Data & AI Engineer – Cyber Risk Intelligence Platform – India/Remote

Data & AI Engineer – Cyber Risk Intelligence Platform – IndiaLocation: India (Remote)About Quantara AI & the RoleQuantara 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 Responsibilities1. 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.