Developer - AI Threat Intel

Arctic Wolf Networks

3 - 8 years

11 - 15 Lacs

bengaluru

Posted:2 days ago| Platform:

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Skills Required

automation backend git information security debugging machine learning workflow distribution system financial services python

Work Mode

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Job Type

Full Time

Job Description

About the Role

Design and develop an AI-driven Threat Intel Platform focused on fraud, risk, and anomaly detection.
Build and extend agentic frameworks using LangChain, LangGraph, or similar architectures for reasoning, orchestration, and task automation.
Design, develop, and maintain backend services and microservices using Python, Go, and cloud-native technologies.
Build secure, scalable, and high-performance systems leveraging AWS services including RDS, DynamoDB, Lambda, EKS/Kubernetes , and event-driven pipelines.
Develop and manage MLOps pipelines for scalable model training, testing, deployment, and real-time inference.
Implement end-to-end automation workflows , from data ingestion and feature engineering to autonomous inference and actioning.
Integrate LLMs and autonomous AI agents for dynamic pattern recognition, event correlation, and decision automation.
Integrate software components into robust, production-ready systems with clear documentation, testing, and maintainability.
Apply test-driven development and CI/CD practices using Git, Jenkins, Terraform, Docker, and cloud-native tooling.
Collaborate with data science, threat intelligence, and platform engineering teams to deliver intelligent, context-aware solutions.
Use advanced debugging and analytical techniques to solve complex distributed-systems and AI workflow challenges.
Mentor junior developers and contribute to team growth through knowledge sharing and technical leadership.
Participate in R&D demos, innovation initiatives, and annual hackathons to explore and showcase new ideas.

About You

3+ years of experience in software engineering, machine learning, or backend/data systems development.
Strong focus on backend engineering with experience building large-scale, distributed, or real-time systems .
Hands-on experience with fraud/risk analytics, behavioral modeling, or anomaly detection (fintech, ad tech, cybersecurity domains preferred).
Proven experience building or integrating agentic AI frameworks (LangChain, LangGraph, Semantic Kernel, etc.).
Strong programming skills in Python (preferred) or Go, and familiarity with PyTorch, TensorFlow, or Scikit-learn.
Experience with cloud-native architectures and tools: Kubernetes, Docker, Terraform , event-driven systems.
Practical knowledge of MLOps , data pipeline design, feature stores, and real-time inference systems.
Understanding of AI automation , LLM-based orchestration, prompt engineering, and evaluation strategies.
Familiarity with cloud platforms (preferably AWS ) and distributed systems at scale.
Proven ability to work independently on large features, drive technical discussions, and deliver production-quality systems.
Strong collaboration and communication skills, with a passion for mentoring and team development.
A proactive mindset and ability to adapt existing approaches to solve new challenges.

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