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Safe Security

AI-powered cybersecurity risk analytics platform

Engineering Manager

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaIn-person

About the Job

Requirements

  • A Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • At least 8 years of software engineering experience, including at least 2 years in an engineering management role.
  • Hands-on experience with server-side technologies such as Node.js, TypeScript, Python, Go, or similar technologies.
  • Understanding of modern web development technologies such as React, Angular, Vue.js, or similar frameworks.
  • Knowledge of SQL and NoSQL databases, including experience optimizing database performance at scale.
  • Experience with cloud-native and distributed systems using technologies such as AWS, ECS/Fargate, S3, SQS, Lambda, RabbitMQ, Kafka/MSK, Redis, Snowflake, ScyllaDB, DynamoDB, MySQL, or PostgreSQL.
  • Experience with observability and production engineering practices using tools such as OpenTelemetry, Sentry, Observe.io, structured logging, metrics, traces, dashboards, and alerts.
  • Practical experience using AI-assisted coding tools such as Cursor, GitHub Copilot, ChatGPT, Claude, or similar tools to improve development productivity and engineering quality.
  • Working knowledge of LLM concepts, including prompt engineering, RAG, agents, vector databases, model evaluation, hallucination mitigation, and LLM-based product workflows.
  • Track record of delivering high-performance, scalable, secure, and reliable platforms in an agile environment.
  • Leadership and communication skills, including mentoring and guiding a team of developers toward technical excellence.
  • Experience managing and coaching teams of 4–8 members and delivering high-quality projects on time.
  • Ability to balance people leadership, delivery ownership, architectural thinking, and hands-on technical depth.

Responsibilities

  • Lead talented engineers by providing technical guidance, mentorship, delivery ownership, and strategic direction.
  • Contribute to solving complex scale, architecture, data, and AI-driven product problems.
  • Collaborate with Product, Design, Platform, DevOps, Security, and other engineering teams.
  • Help design and build core product features aimed at predicting, quantifying, and preventing cyber breaches.
  • Drive modern engineering practices, including AI-assisted coding, effective use of tools such as Cursor, GitHub Copilot, and LLMs, and practical application of LLM-based systems such as RAG, agents, prompt engineering, and evaluation frameworks.
  • Lead, mentor, and inspire a team of engineers, fostering ownership, continuous learning, growth, collaboration, and engineering excellence.
  • Define and execute the team's technical strategy and roadmap, aligning it with business objectives, product priorities, customer commitments, and organizational goals.
  • Conduct code reviews to maintain quality and maintainability, identify refactoring opportunities, and provide feedback, including on AI-generated code.
  • Drive adoption of AI-assisted coding and productivity tools such as Cursor, GitHub Copilot, ChatGPT, Claude, or similar tools for development, testing, debugging, documentation, codebase exploration, and refactoring.
  • Guide teams in applying knowledge of LLMs, prompt engineering, RAG, AI agents, vector stores, model evaluation, and LLM observability responsibly in product and engineering workflows.
  • Troubleshoot and resolve complex technical issues, identify root causes, and implement long-term solutions across microservices, distributed systems, data platforms, and production environments.
  • Collaborate with product managers, designers, architects, DevOps, security, and other stakeholders to align technical solutions with product outcomes, customer needs, and business objectives.
  • Lead planning, execution, and delivery of features, ensuring completion on time, within scope, and to quality standards.
  • Drive innovation and adoption of best practices in development, architecture, testing, observability, security, performance, cost optimization, and AI-native engineering.
  • Support architectural decisions across APIs, microservices, event-driven systems, cloud infrastructure, data stores, and AI-enabled capabilities.
  • Ensure the team owns production quality through observability, incident management, root-cause analysis, bug hygiene, performance tracking, service-level objectives, and continuous reliability improvements.
  • Conduct regular performance evaluations, provide feedback, support professional growth, and coach engineers on technical depth, ownership, communication, and execution.

Desired Qualifications

  • Experience in cybersecurity, enterprise SaaS, risk management, CTEM, TPRM, CRQ, compliance, or related domains.

About the Company

Safe Security

AI-powered cybersecurity risk analytics platform

Safe.Security provides a real-time cyber risk management platform for businesses. It collects and analyzes millions of signals per customer per day using AI to give a live view of an organization's risk posture. The platform connects with 50+ APIs, threat feeds, and user data, uses a Generative AI interface called SafeGPT, and maps risk across the MITRE ATT&CK kill chain to show where an attack could happen. It helps translate security controls into financial exposure for underwriting and guides which security investments to prioritize, with the broader goal of aligning cybersecurity risk with enterprise risk and securing appropriate cyber insurance.

Company size
501-1,000
Company stage
Series C
Total funding
$162.2M
Headquarters
Palo Alto, CA
Founded
2012

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