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

    Quantara AI
    Quantara AI India

    2 days ago

    Human Resources
    Description

    Backend & 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 helping CISOs, Boards, and executive leaders quantify, prioritize, and manage cyber risk in clear business terms. Our platform integrates Cyber Risk Quantification (CRQ), Continuous Threat Exposure Management (CTEM), and AI-driven analytics to enable defensible, data-backed security and investment decisions.

    We are seeking a highly capable Data & AI Engineer with strong Django, Python, and cloud engineering expertise to help build and scale the core data and intelligence layer of our platform. This is a hands-on role focused on rapid model development, automation, and production-grade AI systems.

    You will work across backend systems, data pipelines, and machine learning workflows to deliver a secure, scalable, and intelligent enterprise platform.

    Key Responsibilities

    1. Backend Engineering & Data Modeling


    • Design and develop core backend services using Django and Python


    • Rapidly build and evolve data models for risk, asset, threats, control, and business domains


    • Optimize database schemas and queries for high-performance analytics


    • Implement secure, multi-tenant SaaS architectures


    • Maintain high-quality documentation and coding standards

    2. Data Engineering & Automation


    • Design and operate scalable data pipelines for structured and unstructured data


    • Integrate third-party security, business, and cloud data sources


    • Automate data ingestion, validation, transformation, and enrichment workflows


    • Implement monitoring and reliability frameworks for pipelines


    • Support batch and near-real-time processing

    3. AI / ML / LLM Engineering


    • Build and deploy machine learning and LLM-powered analytics systems


    • Develop RAG pipelines and enterprise knowledge layers


    • Implement embeddings, vector search, and context management


    • Fine-tune and optimize models for production use


    • Integrate AI services into core platform workflows

    4. Risk Quantification Systems


    • Develop automated engines for risk, ROI, RRI, maturity, and performance metrics


    • Embed quantification logic into platform data models


    • Ensure transparency, auditability, and explainability of calculations


    • Support executive reporting and analytics pipelines

    5. Cloud, CI/CD & Operations


    • Build and maintain CI/CD pipelines for backend, data, and AI systems


    • Deploy and manage workloads on AWS infrastructure


    • Implement containerization and environment automation


    • Establish monitoring, logging, and alerting systems


    • Support security, availability, and performance objectives

    Qualifications


    • 6–10 years of experience in backend, data, or AI engineering


    • 6–10 years of experience in Django, Python, Postgres, data modeling & related technologies


    • Proven experience building enterprise SaaS and cybersecurity platforms


    • Advanced SQL and database optimization skills


    • Hands-on experience with ML, LLMs, and automation pipelines


    • Practical AWS experience (EC2, RDS, S3, Lambda, ECS/EKS)


    • Experience with CI/CD and infrastructure automation


    • Strong understanding of data security and system scalability

    Technical Stack Exposure

    • Data & Pipelines:
    • Airflow, dbt, Spark, Pandas, Kafka, Kinesis
    • Backend & Databases:
    • Django, REST APIs, PostgreSQL, MySQL, DynamoDB
    • Cloud & DevOps:
    • AWS, Terraform, Docker, Kubernetes
    • AI / ML / LLM:
    • Hugging Face, LangChain, LlamaIndex, OpenAI APIs, FAISS, Pinecone
    • CI/CD:
    • GitHub Actions, Jenkins, GitLab CI

    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

    • India market-aligned base salary + performance incentives.
    • Open to Contract-to-Hire with full-time conversion based on performance.

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