37mo ago

Tech Lead / Software Development Engineer III

India·BangaloreFull-timemid

OtherSoftware EngineerSoftware Development EngineerSoftware Engineering

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Quick Summary

Overview

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.

Technical Tools

angularawsazureexpressgcpgojavascriptpythonreactsqltypescriptvueagilecode-reviewcybersecuritymentoringmicroservicesproject-management

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.

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.

What We Offer

~4 min read

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.

✓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.

✓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.

✓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.