AI Engineer – Agentic AI & Cloud Discovery

About the role

Pragmatike is hiring AI Engineers for a global enterprise cybersecurity client. The role focuses on turning cutting‑edge LLM and machine‑learning capabilities into reliable, production‑grade security products, working remotely from India.

Key responsibilities

• Design and build LLM‑powered analysis and classification pipelines, then productionize them as Go services.
• Prototype approaches in Python, including prompting strategies, RAG, structured extraction, and ML classifiers, meeting defined accuracy targets.
• Define ground‑truth datasets, evaluation metrics, and regression suites to continuously improve model quality.
• Monitor model quality and drift in production, creating processes to address degradation.
• Collaborate with security researchers to translate attack patterns into detection logic and integrate AI capabilities with event, storage, and UI layers.

Required profile

• 4+ years of software engineering experience, including at least 2 years shipping LLM‑ or ML‑backed features to production.
• Strong Go skills for backend services and strong Python skills for experimentation and data pipelines.
• Hands‑on experience with LLM APIs, prompt engineering, structured outputs, and retrieval‑augmented generation.
• Experience evaluating LLM/ML systems through offline tests, human review, or regression suites.
• Understanding of AI agent architectures, cloud‑native deployment (Docker, Kubernetes) and major cloud platforms (AWS, GCP, Azure).
• Fluent English and proven ability to work independently in a remote‑first environment.

Required skills

• Go
• Python
• LLM APIs and prompt engineering
• Docker & Kubernetes
• AWS, GCP, Azure
• Claude Code, Cursor, GitHub Copilot, Codex (AI coding assistants)
• Vector databases and embedding pipelines
• Model fine‑tuning for classification or extraction
• OpenTelemetry‑style observability

What we offer

• Opportunity to work on a greenfield product at the intersection of cybersecurity and agentic AI.
• Turn cutting‑edge LLM/ML research into production systems protecting enterprise customers.
• Blend AI experimentation with production engineering, from Python prototypes to Go services.
• Take ownership of a key workstream and influence architecture from an early stage.
• Collaborate with a highly technical, distributed team where AI is a core part of the development process.