Pragmatike
AI Engineer – Agentic AI & Cloud Discovery
About this role
Location: India, Remote-First Employment: Full-Time Start Date: November 2026 Experience: 4+ years Language: Fluent English required Industry: Cybersecurity / Enterprise SaaS / AI Security About the Opportunity Pragmatike is recruiting on behalf of a global enterprise cybersecurity company building a new generation of products to secure AI agents, LLM-powered applications, and the data they access. The engineering organization is scaling rapidly in India, with two AI Engineer openings focused on turning AI and machine learning capabilities into reliable, production-grade security products. We're looking for engineers who are equally comfortable building production services in Go and developing LLM/ML pipelines in Python, with the ability to move quickly from experimentation to hardened production systems. You'll join one of two workstreams:
- Agentic AI Forensics: Turn agent traces, prompts, tool calls, and security events into structured, explainable findings for security analysts using LLM reasoning, RAG, structured extraction, and rigorous evaluation.
- Cloud Discovery: Classify cloud resources and workloads to identify AI agents, model endpoints, and AI-enabled applications, while inferring their purpose and security risk using LLM/ML classification at scale. Both workstreams share the same foundations: Go for production services, Python for experimentation and data pipelines, LLM APIs, rigorous evaluation, and cloud-native deployment.
What You'll Do
- 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, and ship solutions that meet defined accuracy targets.
- Define ground-truth datasets, evaluation metrics, and regression suites to continuously measure and improve model quality.
- Monitor model quality and drift in production and build processes to identify and address degradation.
- Collaborate with security researchers to translate attack patterns and risk signals into detection and summarization logic.
- Integrate AI-powered capabilities with event, storage, and UI layers to surface actionable results to security teams.
- Use AI-assisted development workflows to accelerate implementation, testing, debugging, and experimentation. What We're Looking For
- 4+ years of software engineering experience, including 2+ years shipping LLM- or ML-backed features to production.
- Strong Go skills for production backend services and strong Python skills for experimentation and data pipelines.
- Hands-on experience with LLM APIs, prompt engineering, structured outputs, and RAG.
- Experience evaluating LLM/ML systems through offline evaluations, human review, regression suites, or similar approaches.
- Understanding of AI agent architectures, including tool calling, MCP or similar protocols, multi-step planning, and common failure modes.