SPARC is an AI research and engineering lab focused on building secure, sovereign, and continuously improving AI systems. We operate at the frontier of AI and security, driven by a two-fold mission:

- Self-improving AI: We advance AI systems that improve through experience—learning from interaction, refining their reasoning, and growing more capable over time.
- Secure-by-Design Infrastructure: We develop the foundations for AI infrastructure that is secure by design, verifiable at scale, and resilient enough for deployment in critical sectors such as defence, healthcare, finance, and national infrastructure.

Cybersecurity serves as our proving ground. It provides objective feedback, rapidly evolving environments, and adaptive adversaries, making it one of the most demanding domains for developing autonomous AI systems. Success in this setting pushes the frontier of AI itself, advancing systems that can reason, adapt, and operate reliably in complex real-world settings. At SPARC, you'll work on fundamental research and engineering challenges while building AI systems designed to solve problems of national and strategic importance. This is a place for those who want to move beyond incremental work and contribute to systems that matter.

Role Overview

As an AI Engineer, you will build the software systems that power next-generation AI for cybersecurity. You will develop the infrastructure that enables rapidly training, evaluating, and deploying large language models and autonomous AI agents at scale. This role spans AI infrastructure, distributed systems, model serving, evaluation platforms, and agent runtimes. You will work closely with research scientists to transform cutting-edge algorithms into reliable, production-quality systems.

What you will work on

- AI Infrastructure.



Build scalable infrastructure for training, evaluating, and deploying foundation models and autonomous AI agents. Develop high-performance inference and model serving systems for large language models. Design distributed compute, storage, and orchestration systems for AI workloads.
- Agent Platforms. Build agent runtimes supporting planning, tool use, memory, verification, and long-horizon execution. Develop infrastructure for agent orchestration, task scheduling, and execution across diverse environments. Create reusable frameworks that enable rapid experimentation with new agent capabilities.
- Evaluation and Experimentation. Build scalable evaluation pipelines and benchmark infrastructure for AI models and autonomous agents. Develop tooling for experiment management, data collection, telemetry, and performance analysis. Improve reproducibility, observability, and reliability of AI experimentation.
- Production Systems. Productionize research prototypes into robust, maintainable software systems. Build APIs, developer tools, and internal platforms that accelerate AI research and deployment. Optimize systems for performance, scalability, and reliability across large-scale deployments.

Qualifications We are looking for engineers with strong software engineering fundamentals and expertise in one or more of the following areas:

- AI/ML Systems
- Large Language Model Inference and Serving
- Distributed Systems
- Agent Frameworks and AI Infrastructure
- Cloud Infrastructure and Container Orchestration
- Data Processing Pipelines
- Python, C++, Go, or Rust

Experience with modern AI infrastructure such as distributed training, model serving, inference optimization, evaluation frameworks, or large-scale production AI systems is highly desirable.

📌 Artificial Intelligence Engineer (Bengaluru)
🏢 SPARC (Security, Privacy and AI Research Centre)
📍 Bengaluru