Job Overview:
As an Engineering Manager, you will:
- 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 closely 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 usage of tools like Cursor / GitHub Copilot / LLMs, and practical application of LLM-based systems such as RAG, agents, prompt engineering, and evaluation frameworks.
Core Responsibilities
Technical Leadership: Lead, mentor, and inspire a team of engineers, fostering a culture of ownership, continuous learning, growth, collaboration, and engineering excellence.
Technical Strategy: Define and execute the technical strategy and roadmap for your team, aligning it with business objectives, product priorities, customer commitments, and organizational goals.
Code Review: Conduct thorough code reviews to maintain code quality, improve maintainability, identify refactoring opportunities, and provide constructive feedback to team members, including on AI-generated code.
AI-Assisted Engineering: 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.
LLM Awareness: Bring practical knowledge of LLMs, prompt engineering, RAG, AI agents, vector stores, model evaluation, and LLM observability, and guide teams in applying these concepts responsibly in product and engineering workflows.
Problem Solving: Troubleshoot and resolve complex technical issues, identify root causes, and implement effective long-term solutions across microservices, distributed systems, data platforms, and production environments.
Collaboration: Collaborate closely with product managers, designers, architects, DevOps, security, and other stakeholders to ensure alignment between technical solutions, product outcomes, customer needs, and business objectives.
Project Management: Lead the planning, execution, and successful delivery of features, ensuring they are completed on time, within scope, and to the highest quality standards.
Technical Excellence: Drive innovation and adoption of best practices in development, architecture, testing, observability, security, performance, cost optimization, and modern AI-native engineering practices.
Architectural Guidance: Be a thoughtful technical voice and support your team in making diligent architectural decisions across APIs, microservices, event-driven systems, cloud infrastructure, data stores, and AI-enabled capabilities.
Production Ownership: Ensure your team owns production quality through observability, incident management, RCA, bug hygiene, performance tracking, SLOs, and continuous reliability improvements.
Performance Management: Conduct regular performance evaluations, provide feedback, support professional growth, and coach engineers on technical depth, ownership, communication, and execution.
Qualifications/ Essentials Skills/ Experience
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Minimum of 8 years of proven experience in software engineering, with at least 2 years in an engineering management role.
Strong hands-on experience in server-side technologies such as Node.js, TypeScript, Python, Go, or similar technologies.
Strong understanding of modern web development technologies such as React, Angular, Vue.js, or similar frameworks.
Strong knowledge of SQL and NoSQL databases, with experience optimizing database performance at scale.
Experience with modern 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.
Good working knowledge of LLM concepts, including prompt engineering, RAG, agents, vector databases, model evaluation, hallucination mitigation, and LLM-based product workflows.
Demonstrated track record of delivering high-performance, scalable, secure, and reliable platforms in a fast-paced agile environment.
Exceptional leadership and communication skills, with a strong drive to mentor and guide a team of developers toward technical excellence.
Experience managing and coaching 4-8 member teams and delivering high-quality projects on time.
Ability to balance people leadership, delivery ownership, architectural thinking, and hands-on technical depth.
Experience in cybersecurity, enterprise SaaS, risk management, CTEM, TPRM, CRQ, compliance, or related domains is a plus.

