Lead Software Engineer

At Seezo, we build at the intersection of AppSec and GenAI to make world-class security accessible to every engineering team. We're seeking a Lead Software Engineer to help us advance the capabilities of our GenAI-powered security platform.

Sandesh (ex-Head of Security @ Razorpay) and Rakshitha (ex-Head of Customer Success @ PingSafe) founded Seezo. With over 20 years of Cybersecurity experience, they have a deep understanding of the challenges faced by security teams and are committed to solving them. We are funded by Accel, one of India’s largest global VC firms. 

Seezo's culture

• Writing is Thinking: Most teams rely on Slack. At Seezo, our operating system is Google Docs. Documenting helps us clarify our thoughts, communicate better, and build with intention.
• Proactive involvement: If you'd like to try a quick experiment, discuss branding, or improve a workflow, go ahead. We value Proactivity in work and communication.
• Love for Security: Security is not just a feature; it is the foundation of what we do. We prioritize Security in every engineering decision we make.
• Engineering first: Many companies claim to be engineering-first, but for us, it is a daily reality. Our team regularly dives deep into topics such as testing practices and architecture. Quality matters at every step.
• Open opinion exchange: We value different opinions. Ideas flow freely, backed by facts, experience, and sometimes emotion. Every discussion remains respectful and constructive, regardless of how spirited it becomes.

The opportunity

• As a Lead Engineer at Seezo, you will play a key role in advancing our GenAI platform for cybersecurity. You will work at the intersection of applied AI, LLM Ops software engineering, and security tooling, helping to build, scale, and operationalize innovative solutions that are used by engineering teams everywhere.
• You will be part of a team that moves quickly. This is a unique opportunity to learn, contribute, and see your work have an immediate impact in a high-ownership environment.

The challenge

Your mission at Seezo will include

• Building and operationalizing LLM Evals pipelines for cybersecurity applications
• Fine-tuning, deploying, and managing LLMs for security-focused use cases
• Designing and maintaining robust, scalable software systems to support AI-driven workflows across cloud and on-prem environments
• Implementing monitoring, tracing, and observability for LLM performance, reliability, and drift in production
• Creating security-focused benchmarks and test sets using the latest AI models and ensuring reliable automated test coverage
• Integrating LLM workflows into Seezo, including code & Cloud Infra scanning
• Developing AI agents for automating security requirement validations
• Architecting and deploying complex applications across AWS, Azure, GCP, and customer on-premises infrastructure
• Solving scaling and reliability challenges for both AI and traditional software systems, ensuring robust performance as we grow

Why you'll love it here

• Impact: Shape AI-powered security solutions used by real engineering teams
• Innovation: Work with the latest in GenAI, LLMOps, and software engineering methodologies
• Growth: Learn quickly in a fast-paced, hands-on startup environment with exposure to both AI and full-stack engineering
• Ownership: Influence product decisions, software architecture, and technical direction from day one
• Learning: Dive deep into applied AI, Cybersecurity, cloud, and on-prem infrastructure, and large-scale distributed systems

You'll thrive here if you

• Have a solid foundation or strong interest in AI, Machine Learning, or GenAI
• Bring experience or enthusiasm for building and maintaining complex software systems
• Enjoy designing, evaluating, and deploying AI models and scalable backend services in real-world scenarios
• Are motivated by the challenge of making AI and software work for complex security problems at scale
• Like to take initiative, own your projects, and learn new technologies quickly
• Appreciate the operational and engineering complexity of building robust systems for Cybersecurity

Bonus Points For

• Experience with LLMOps, observability, or monitoring in ML pipelines and distributed systems
• Personal or academic projects involving LLMs, GenAI, or large-scale software engineering
• Background or interest in cybersecurity, secure software development, or infrastructure-as-code
• Familiarity with Prompt Engineering, RAG, frameworks like DSPy, or scalable deployment patterns
• Open-source contributions, blogging, or sharing your work and ideas with the tech community

About the hiring process

After a short evaluation task, you can expect two to three interviews focusing on your technical ability and cultural fit. Irrespective of the outcome, for every candidate we interview, we will provide feedback and the rationale for our decision.

Join us to help define the future of cybersecurity and software engineering with AI!