Tech Lead / Software Development Engineer III

Most boards and executives are currently flying blind when it comes to cyber risk. They are guessing. At Safe, we’ve built an AI-driven engine that finally gives the C-Suite a clear, quantified, and real-time view of their security posture. We don’t just provide data; we provide certainty. We are a $170M Series C-funded category leader. We don’t play in the mid-market; we operate at the highest levels of global enterprise. Today, we are proud to serve 10% of the Fortune 500, protecting global icons such as Apple, Netflix, AT&T, Verizon, and Victoria’s Secret. As we scale toward our next chapter, we are looking for high-performers who want to do the best work of their careers at the intersection of AI and Cybersecurity. The Culture Memo: Our Operating System Safe is not a typical corporate environment. We are a high-intensity, mission-driven team. We value builders who want to define a category and work alongside people who are equally committed to excellence. Extreme Ownership: We don’t do "not my job." We hire people who see a gap and own the solution from start to finish. The Elite Standard: We serve the most sophisticated companies on the planet. Our work must be bulletproof. Whether it’s a line of code or a sales deck, we aim for Tier-1 quality every time. Methodology & Rigor: We don’t wing it. From Force Management and MEDDICC in sales to data-driven sprints in engineering, we rely on proven frameworks to stay disciplined and predictable. Radical Candor: We move too fast for politics or sugar-coating. We value direct, honest feedback that helps us find the right answer quickly. The Series C Hustle: We have the stability of a well-funded leader but the heart of a startup. The Perks & Ownership: We want our team to feel like owners because they are owners. We trust our people to manage their results and their time. Meaningful Equity: Every "Safestar" is a shareholder. You aren’t just an employee; you are a partner in our success. Unlimited Leaves: We don’t believe in clock-watching. We offer unlimited leave because we trust you to take the time you need to recharge while staying committed to the mission. Comprehensive Benefits: We provide top-tier medical insurance and wellness benefits to ensure you and your family are well cared for. Career Trajectory: We are growing aggressively. For high-performers, the path for advancement moves at the speed of your ambition.

Job Overview: We are seeking an experienced and passionate Engineer to join our engineering team. As a senior engineer, you will lead a high-performing engineering team working closely with our Design, Product, and other stakeholders to develop and deliver core product features that help in predicting and preventing cyber breaches.    Location: Bengaluru

Core Responsibilities: Technical Leadership: Provide technical leadership and mentorship to engineers, promoting engineering best practices, high code quality, and continuous improvement. Architecture and Design: Collaborate with cross-functional teams to design and architect scalable, secure, and high-performance multi-tenant services and systems. Code Review: Conduct thorough code reviews, identify opportunities for improvement, and provide constructive technical feedback to engineers. Cloud Expertise: Leverage AWS services such as Lambda, API Gateway, EC2, S3, RDS, and other appropriate cloud technologies to architect and optimize cloud-based solutions. Problem Solving: Troubleshoot complex technical problems, identify root causes, and design effective and scalable solutions. Collaboration: Work closely with Product, Design, Engineering, and other stakeholders to ensure technical solutions are aligned with product and business objectives. Project Execution: Lead the planning, execution, and successful delivery of features while maintaining engineering quality and predictable delivery. Experience/ Qualifications/ Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 5+ years of software engineering experience, including experience operating as a Senior Engineer or Lead Engineer. Strong expertise in at least one server-side programming language such as Node.js, Python, or Go . Hands-on experience designing and developing APIs and backend services. Experience with TypeScript and frameworks such as Express is preferred. Good understanding of SQL and NoSQL databases and their appropriate use across different workloads. Strong understanding of cloud computing concepts and hands-on experience with a major cloud provider such as AWS, GCP, or Azure . Experience building and deploying applications in containerized environments . Proven track record of building and delivering high-performance and scalable platforms in a fast-paced engineering environment. Strong understanding of system design, distributed systems, scalability, reliability, and multi-tenant architectures . Strong leadership and communication skills, with the ability to lead and mentor engineers toward technical excellence. Strong problem-solving and critical-thinking abilities. High degree of ownership with the ability to drive problems from definition through production delivery. Understanding of DevOps practices and Infrastructure as Code technologies such as AWS CloudFormation is advantageous. AI / LLM Skills: Strong working knowledge of Generative AI and LLM fundamentals , including how LLMs work, tokens, context windows, prompting, hallucinations, embeddings, and common model limitations. Hands-on experience using AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot, or equivalent, with the ability to critically review and validate AI-generated code, tests, and technical solutions. Understanding of common LLM application patterns , including structured outputs, tool/function calling, retrieval-augmented generation (RAG), and agentic workflows. Ability to make informed engineering decisions about when to use deterministic software, a direct LLM call, retrieval/RAG, or an agentic approach , based on the problem being solved. Ability to define how AI-powered capabilities should be evaluated , including the use of golden datasets, appropriate accuracy metrics, regression testing, human evaluation, and LLM-as-a-judge where appropriate. Ability to reason about production AI trade-offs , including accuracy, latency, cost, reliability, security, and observability.