AI Engineer

A high-growth Cyber & Deep-Tech innovator operating at the forefront of Identity Security and enterprise AI. The company engineers an advanced AI-powered platform utilizing state-of-the-art LLMs to govern, visualize, and protect both human and non-human identities across complex enterprise infrastructures.

Through automated graph analytics and autonomous agent systems, the platform continuously maps permission hierarchies, detects anomalies, and drastically reduces organizational attack surfaces.

Backed by substantial funding from premier global venture capital firms, the organization combines significant market momentum with deep technical innovation.

The company is located in the Central region near the light rail line and operates on a flexible hybrid work model with one day working from home.

Role Description-

• Serving as a Senior AI / LLM Software Engineer, taking end-to-end technical ownership over the platform’s intelligent layer, including autonomous agent frameworks, conversational AI assistants, and proactive security graph reasoning engines.
• Driving core AI engineering initiatives (accounting for roughly 60–70% of the role), encompassing advanced Prompt Engineering, Orchestration, Agentic Systems, RAG architectures, Semantic Search, and Hybrid Retrieval.
• Building robust continuous evaluation pipelines (LLM Evals, Benchmarks, Human-in-the-Loop workflows) and designing mechanisms to detect and mitigate LLM failure modes, hallucinations, and edge cases in mission-critical production environments.
• Architecting and maintaining scalable backend software services and data pipelines in Python, handling schema design, workflow structuring, and end-to-end system integration.
• Optimizing production LLM infrastructure with a strong focus on runtime performance, Latency reduction, API cost efficiency, deployment orchestration, and system observability.
• Collaborating cross-functionally with Core Security Researchers, Backend Engineers, and Product teams to translate complex enterprise identity relationships into structured, actionable intelligence.

Requirements-

• Extensive hands-on software development experience in Python (5+ years), building production-grade distributed backend systems – Mandatory
• Hands-on professional background in AI Engineering / LLM Application Development (1+ years), including a deep understanding of data design for AI, structured schemas, prompt engineering, and workflow structuring – Mandatory
• Proven experience building production applications utilizing LLMs, Orchestration frameworks (e.g., LangChain, LlamaIndex), or Agentic workflows – Mandatory
• Hands-on expertise with Retrieval-Augmented Generation (RAG), Semantic Search, and Hybrid Retrieval architectures – Significant Advantage
• Practical understanding of LLM evaluations (evals), benchmark design, and observability/monitoring for generative models in production – Significant Advantage
• Solid foundations in cloud-native infrastructure, API development, data modeling, and performance optimization (latency and cost management) – Mandatory
• Background or strong interest in Cybersecurity, Cloud Security, or Identity Governance (IAM/CIEM/NHI) – Advantage
• Degree in Computer Science, Software Engineering, or a related quantitative field – Advantage

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