SOFTWARE ENGINEER (DJANGO / PYTHON) - SECURITY

Step in as the engine behind their Intelligence Operations. You will build and scale the high-throughput Python (Django) Backend that Collects, Processes & Analyses Large Volumes of Threat Telemetry. By operationalising Complex Data Pipelines & Integrating LLM Workflows, you will directly fuel the Research that enables our enterprise clients to outmanoeuvre Real-World Adversaries., * Engineer and scale the internal Python / Django-Based Threat Intelligence Platform, ensuring it remains highly resilient while handling massive volumes of Real-Time Security Data.

• Automate complex pipelines that Ingest, Normalise & Process Diverse internal & External Threat Intelligence Sources.
• Optimise Core Workflows & Codebases, leveraging Celery & Kubernetes to continuously maximize efficiency, performance, and reliability.
• Innovate by Designing & Operationalising LLM-Powered Workflows to accelerate Intelligence gathering and amplify Security Operations.
• Maintain absolute Operational Resilience, ensuring platform uptime, monitoring, and logging support 24/7 Threat Intelligence Operations

Searches: Python Developer / Django / Software Engineer / Data Engineer / LLM / Elasticsearch / OpenSearch / Kubernetes / Celery

• The Threat Data Architect: A hungry BackEnd Engineer who thrives on building scalable, reliable systems capable of ingesting and normalising massive Security Datasets without buckling under pressure.
• The Intelligence Automator: You don't just move data; you weaponize it. You have a deep interest in the Cyber Security Domain and want to leverage Kubernetes, Celery & LLM APIs to Automate and scale complex Threat Intelligence Workflows.

Skills & Experience:

• Backend Engineering (3-5 Years): High proficiency in Python (Django), with a proven track record of building scalable, maintainable systems within a high-growth environment.
• Threat Intel / Cyber Domain: Experience working within the cybersecurity space, specifically building or supporting systems that process and analyse security data.
• Infrastructure & Orchestration: Proven experience Designing Task Orchestration Frameworks (Celery), Containerization (Kubernetes) & Deploying via CI/CD Pipelines in Cloud environments (AWS / GCP / Azure).
• Big Data & Search: Solid experience building large-scale Data Ingestion Pipelines and integrating robust Search / Analytics Platforms like Elasticsearch or OpenSearch.
• AI / LLM Integration: Practical Exposure to leveraging LLM APIs (Open AI, Anthropic) as Productivity Amplifiers to Automate Processes & Scale Security Workflows.
• Start-Up Execution: A proactive, ownership-driven mindset comfortable navigating ambiguity and fast-changing priorities within an early-stage B2B scale-up.