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

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

Quantara AISurat, IN
7 days ago
Job type
  • Remote
Job description

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.
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