AI Engineer – Agentic AI & Cloud Discovery

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:

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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.

- Experience with cloud-native deployment using Docker, Kubernetes , and AWS, GCP, or Azure.

- Fluent English with strong written and verbal communication skills.

- Comfortable using modern AI coding assistants such as Claude Code, Cursor, GitHub Copilot, Codex, or similar. This is a must-have.

- Strong ownership and the ability to work independently in a remote-first, distributed environment.

Nice to Have

- Background in security analytics, SIEM/SOAR, or digital forensics .

- Practical knowledge of major cloud provider APIs, IAM models, and resource inventory.

- Experience with vector databases, embedding pipelines, or model fine-tuning for classification or extraction.

- Familiarity with tracing AI applications and OpenTelemetry-style observability.

- Previous experience in cybersecurity, security tooling, or trust & safety.

- Experience introducing AI-assisted or agentic development workflows across engineering teams.

AI-First Engineering

AI is a core part of the engineerin