7-10years
Bangalore
Full-Time
Role Overview
We are looking for an experienced and hands-on Engineering Manager to lead high-performing engineering teams responsible for building scalable, reliable, and secure software products.
The ideal candidate should have strong technical expertise across Node.js, React, and Python , excellent system design and architecture capabilities, and exceptional debugging and problem-solving skills . This role requires someone who can comfortably move between people leadership, architecture discussions, production troubleshooting, code reviews, and delivery management.
The Engineering Manager will be accountable not only for delivering projects but also for establishing a strong engineering culture focused on quality, ownership, performance, reliability, security, and continuous improvement .
Key Responsibilities
Engineering & Technical Leadership
Lead and mentor a team of software engineers, senior engineers, and technical leads.
Provide hands-on technical leadership across Node.js, React, Python, APIs, databases, distributed systems, and cloud-native applications .
Participate in architecture and system design discussions and ensure solutions are scalable, maintainable, secure, and cost-effective.
Review technical designs, architecture documents, APIs, database designs, and critical code changes.
Establish and enforce engineering standards, coding guidelines, design principles, and development best practices.
Identify technical debt and develop practical strategies for reducing it without impacting business delivery.
Drive appropriate adoption of modern technologies, frameworks, engineering tools, and AI-assisted development practices.
Debugging & Problem Solving
Debugging excellence is a critical requirement for this role.
Demonstrate exceptional ability to diagnose complex application and production issues across frontend, backend, database, infrastructure, and integrations.
Troubleshoot problems across React → APIs → Node.js/Python services → databases → queues/events → cloud infrastructure .
Analyze logs, traces, metrics, database queries, network requests, memory/CPU utilization, and application behavior to identify root causes.
Handle complex issues including performance degradation, memory leaks, race conditions, concurrency problems, API failures, database bottlenecks, integration failures, and distributed-system issues.
Lead investigation of critical production incidents and drive systematic Root Cause Analysis (RCA) .
Ensure RCAs result in permanent corrective and preventive actions rather than temporary fixes.
Mentor engineers on structured debugging methodologies and systematic problem-solving.
Establish strong observability practices including logging, monitoring, tracing, alerting, and application performance monitoring.
Software Development Expertise
The candidate should have strong practical experience with:
Backend
Node.js and modern JavaScript/TypeScript
Python and commonly used Python frameworks
REST APIs and service-oriented/microservices architectures
Asynchronous and event-driven processing
API design, versioning, authentication, authorization, and security
Caching, messaging, queues, and background processing
Frontend
React and modern frontend architecture
JavaScript/TypeScript
State management and component architecture
Frontend performance optimization
API integration
Browser debugging and profiling
Data
Relational databases such as PostgreSQL/MySQL
Database schema and data-model design
Query optimization and indexing
Transactions, locking, concurrency, and database performance troubleshooting
Familiarity with NoSQL, caching, and search technologies is desirable.
Architecture & System Design
Design and review scalable systems capable of supporting growing users, transactions, tenants, and data volumes.
Strong understanding of microservices, distributed systems, event-driven architecture, API-first design, and cloud-native architectures .
Make appropriate architectural trade-offs between scalability, reliability, complexity, cost, and time-to-market.
Understand multi-tenant SaaS architecture and data isolation patterns.
Drive resilience through fault tolerance, graceful degradation, retry strategies, idempotency, circuit breakers, and appropriate disaster-recovery mechanisms.
Ensure systems are designed with security, observability, maintainability, and operability from the beginning.
Cloud, DevOps & Reliability
Strong understanding of cloud platforms, preferably AWS .
Working knowledge of containers, Docker, Kubernetes/ECS or equivalent orchestration platforms.
Understand CI/CD pipelines and modern software delivery practices.
Promote Infrastructure-as-Code and automated deployment practices.
Establish appropriate monitoring, alerting, logging, tracing, and operational dashboards.
Drive improvements in availability, reliability, performance, scalability, and cloud cost efficiency.
Establish and track appropriate SLIs, SLOs, and operational metrics.
Security
Ensure secure coding and application security practices are followed throughout the engineering lifecycle.
Strong understanding of authentication, authorization, OAuth/OIDC, JWT, API security, encryption, secrets management, and common application vulnerabilities.
Promote security-by-design and appropriate security reviews.
Ensure vulnerabilities and security findings are prioritized and remediated appropriately.
Engineering Quality
Establish high standards for code quality, maintainability, and testability.
Drive effective code-review practices.
Promote unit, integration, API, end-to-end, regression, performance, and security testing.
Improve automated test coverage while focusing on meaningful rather than purely numerical coverage.
Establish appropriate quality gates within CI/CD pipelines.
Reduce production defects and recurring incidents through engineering improvements.
Promote a strong "you build it, you own it" engineering culture.
Delivery & Execution
Own engineering delivery from requirements and technical planning through production rollout.
Convert business requirements into realistic engineering plans and milestones.
Work closely with Product Managers, Architects, QA, DevOps, Security, UX, and other stakeholders.
Identify technical and delivery risks early and establish mitigation plans.
Ensure predictable delivery without compromising engineering quality.
Manage dependencies across teams and systems.
Participate in sprint planning, estimation, backlog refinement, retrospectives, and release planning.
Balance feature delivery, technical debt, platform improvements, security, and operational requirements.
People Leadership
Hire, develop, mentor, and retain strong engineering talent.
Conduct regular 1:1s and provide actionable technical and career feedback.
Define clear expectations and hold engineers accountable for outcomes.
Identify skill gaps and create development plans.
Develop senior engineers and technical leads into stronger technical leaders.
Build a culture of ownership, collaboration, transparency, continuous learning, and engineering excellence.
Manage performance objectively and address performance issues proactively.
Create an environment where engineers can challenge technical decisions constructively.
Incident & Production Management
Take technical ownership during critical production incidents.
Coordinate engineering teams during incident investigation and resolution.
Ensure clear communication with business and technical stakeholders.
Drive blameless but accountable post-incident reviews.
Track corrective actions until completion.
Identify recurring incident patterns and eliminate systemic causes.
AI & Modern Engineering Practices
Encourage effective use of AI-assisted development tools for coding, testing, debugging, documentation, and engineering productivity.
Understand practical applications of Python and modern AI/LLM-based services.
Evaluate AI-generated code critically for correctness, security, maintainability, and performance.
Identify opportunities where automation and AI can improve engineering productivity and software quality.
Required Experience & Skills
8+ years of software engineering experience, with 2+ years in an Engineering Manager, Technical Lead, or equivalent leadership role .
Strong hands-on expertise in Node.js .
Strong experience with React and modern frontend development.
Strong working knowledge of Python .
Excellent debugging and production troubleshooting skills.
Strong understanding of APIs, microservices, distributed systems, and event-driven architectures.
Strong database fundamentals, preferably PostgreSQL/MySQL.
Experience building and operating production systems in cloud environments, preferably AWS.
Strong understanding of CI/CD, automated testing, observability, and DevOps practices.
Strong understanding of software security fundamentals.
Experience managing engineering teams and delivering complex software products.
Excellent analytical, communication, stakeholder-management, and decision-making skills.
Strongly Preferred
Experience building B2B SaaS or multi-tenant platforms .
Experience with high-scale distributed applications.
Experience modernizing legacy applications into modern cloud-native architectures.
Experience with PostgreSQL, Redis, Kafka or similar messaging/event technologies.
Experience with Docker and Kubernetes/ECS.
Experience implementing observability using tools such as OpenTelemetry, APM platforms, centralized logging, and distributed tracing.
Experience working with AI/LLM integrations or AI-assisted software engineering.
Experience managing production systems with high availability requirements.
What We Expect From This Role
The Engineering Manager should be someone who:
Can debug a critical production problem , not just delegate it.
Can challenge an architecture and explain the trade-offs.
Can review code and identify design, performance, security, and maintainability problems.
Can mentor engineers and technical leads.
Can communicate effectively with both engineers and business stakeholders.
Can balance speed with engineering quality .
Takes ownership of production reliability and customer impact.
Makes decisions based on data and engineering fundamentals rather than assumptions.
Builds teams that can operate effectively without constant managerial intervention.
Success Measures
Success in this role will be measured through:
Predictability and quality of engineering delivery.
Reduction in production defects and recurring incidents.
Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR).
Application performance and system reliability.
Engineering productivity and deployment effectiveness.
Technical debt reduction.
Security and quality improvements.
Team capability, retention, and development.
Effectiveness of technical decision-making and architecture.
Ownership and accountability demonstrated by the engineering team.
Required Skills
python team management Good communication SQL Node Js LangChain
