Accountabilities

Engineering Team Leadership: Lead, mentor, and develop a backend engineering team through regular one-to-one meetings, performance management, recruitment, and career development initiatives.
Delivery and Roadmap Ownership: Take responsibility for engineering delivery, including project scope, prioritization, sequencing, risk management, and timely execution of the technical roadmap.
Team Enablement: Identify and remove technical and operational blockers, manage dependencies, facilitate design decisions, and ensure the team can work efficiently toward its objectives.
Customer Communication and Support: Collaborate with customers, support teams, product managers, and engineers to communicate technical issues clearly, investigate problems, assess their impact, and coordinate effective solutions or workarounds.
Customer Escalation Management: Take ownership of customer escalations by participating in technical discussions, setting clear expectations, coordinating engineering responses, and ensuring issues are resolved and communicated effectively.
Technical Architecture and Design: Maintain high standards across backend architecture, code reviews, testing, and production readiness. Guide decisions involving services, databases, messaging systems, and distributed infrastructure.
Technical Collaboration: Partner with senior software engineers and technical leads on architecture proposals, technical RFCs, incident investigations, and long-term engineering strategy.
Cloud Infrastructure and Production Operations: Ensure the team can reliably deploy, roll back, monitor, and troubleshoot services running on Google Cloud Platform (GCP) and DigitalOcean.
Incident Management: Lead production incident response and ensure appropriate follow-up actions, root-cause analysis, and continuous improvements following service disruptions or customer-impacting issues.
Engineering Best Practices: Establish and maintain effective engineering practices, including design reviews, on-call processes, observability, technical documentation, and operational ownership.
AI-Driven Engineering: Encourage the effective use of AI tools for coding, code reviews, testing, and documentation while ensuring engineers remain accountable for the quality and reliability of their work.

Requirements

Bachelor's degree in Engineering (BE/BTech) or a related technical discipline.
8+ years of professional software engineering experience, including experience as an Engineering Manager or technical lead with direct people management responsibilities.
Proven experience leading backend engineering teams and owning the delivery of production-grade software services.
Strong technical understanding of distributed backend systems, including APIs, microservices, gRPC, Kafka or equivalent messaging technologies, databases, and caching solutions.
Hands-on experience with Node.js (JavaScript/TypeScript) and/or Go, with the ability to review technical designs, assess code quality, and support engineers in debugging complex issues.
Experience designing, deploying, and operating services on public cloud platforms, preferably Google Cloud Platform (GCP) and/or DigitalOcean.
Familiarity with cloud-native technologies and delivery tools such as Docker, Kubernetes, Jenkins, GitHub Actions, and Argo.
Knowledge of databases and data technologies such as MongoDB, ClickHouse, Redis, and Memcached.
Experience with production monitoring and troubleshooting using logs, metrics, traces, and observability platforms such as Grafana or equivalent tools.
Proven ability to manage customer-facing technical escalations, including issue investigation, triage, stakeholder communication, and resolution.
Excellent communication and interpersonal skills, with the ability to explain complex technical issues to customers and communicate engineering trade-offs clearly to senior leadership.
Strong leadership, decision-making, prioritization, and problem-solving abilities, with a focus on team development and operational excellence.
Familiarity with AI-powered development assistants for coding, testing, reviewing, and documentation, while maintaining high engineering quality standards.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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