
Staff Backend Engineer - Conversations
HighLevel · India
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- Hybrid
- Full-time
- $200,000 / year
- India
Job highlights
- Own and scale data systems for messaging.
- Design, code, and review database architecture.
- Manage billions of documents across databases.
- Improve reliability and performance of systems.
- Shape engineering culture and technical standards.
About the role
About HighLevel:
HighLevel is an AI-powered, all-in-one white-label sales & marketing platform that empowers agencies, entrepreneurs, and businesses to elevate their digital presence and drive growth. We are proud to support a global and growing community of over 1 million businesses, comprised of agencies, consultants, and businesses of all sizes and industries. HighLevel empowers users with all the tools needed to capture, nurture, and close new leads into repeat customers. As of mid 2025, HighLevel processes over 4 billion API hits and handles more than 2.5 billion message events every day. Our platform manages over 470 terabytes of data distributed across five databases, operates with a network of over 250 micro-services, and supports over 1 million hostnames.
Our People
With over 1,500 team members across 15+ countries, we operate in a global, remote-first environment. We are building more than software; we are building a global community rooted in creativity, collaboration, and impact. We take pride in cultivating a culture where innovation thrives, ideas are celebrated, and people come first, no matter where they call home.
Our Impact
As of mid 2025, our platform powers over 1.5 billion messages, helps generate over 200 million leads, and facilitates over 20 million conversations for the more than 1 million businesses we serve each month. Behind those numbers are real people growing their companies, connecting with customers, and making their mark - and we get to help make that happen.
Role Summary:
We’re hiring a Staff Engineer – Backend (Data Systems) to own and evolve the data backbone that powers messaging at scale inside HighLevel’s Conversations platform.
You’ll design, operate, and scale systems that handle billions of documents across MongoDB, Firestore, Redis, and ElasticSearch — with reliability, predictability, and engineering clarity as non-negotiables.
This is a hands-on IC role — you’ll code, design, review, and guide. You’ll set the standard for how we think about databases, APIs, and engineering craft.
The goal: make our data systems boring in the best possible way — predictable, fast, and easy to trust.
Your first project will be to re-architect and scale ElasticSearch to handle billions of documents efficiently while setting best practices for schema design, observability, and testing discipline across the org.
Team & Project Overview:
You’ll join the Conversations team — the core communication platform at HighLevel that powers SMS, Email, WhatsApp, and DMs for millions of users.
The system processes 2B+ messages monthly, spanning 50+ workloads and thousands of pods across GCP (GKE, Pub/Sub, Cloud Tasks).
The data stack includes MongoDB, Firestore, Redis, ElasticSearch, and ClickHouse — distributed, high-volume, and mission-critical.
This role sits at the intersection of data architecture and engineering culture — scaling systems while shaping how engineers design, test, and reason about them.
Responsibilities:
- Database architecture: Redesign and optimize data models, queries, and indexing strategies across MongoDB, Firestore, and ElasticSearch.
- Search at scale: Own ElasticSearch reliability — ingestion, indexing, shard strategy, and query performance for billions of documents.
- Reliability & performance: Eliminate bottlenecks, improve replication health, and enforce predictable query and index latency.
- System design: Define data flow and integration boundaries between storage, cache, and APIs with clear contracts and fault isolation.
- Observability: Build visibility into every data path — metrics, traces, slow query logs, replication lag, and cluster health dashboards.
- Testing & quality: Make testing non-negotiable — enforce unit, integration, and load testing standards across all backend modules.
- Engineering culture: Drive RFCs, ADRs, and design reviews that push clarity and precision. Codify patterns that make good engineering repeatable.
- Hands-on leadership: Write code, design systems, and debug production issues. Lead by technical example, not by delegation.
- Mentorship & influence: Level up engineers around you — reviews that teach, feedback that sticks, and systems that outlive individuals.
Requirements:
- 8+ years of backend engineering experience with deep database expertise.
- Proven success with ElasticSearch, MongoDB, or Firestore at massive scale.
- Strong understanding of indexing, query optimization, caching, and consistency models.
- Expert in Node.js (TypeScript) and comfortable designing scalable microservices.
- Cloud experience with GCP (GKE, Pub/Sub, Cloud Tasks) or similar distributed infra.
- Practical knowledge of observability: Grafana, Kibana, OpenTelemetry.
- Passion for code quality and process: testing discipline, documentation, and design rigor.
- A track record of shaping team culture — setting standards through RFCs, ADRs, and clear technical writing.
- No tolerance for regressions, unclear ownership, or untested systems.
Nice to Have:
- Experience with ElasticSearch cluster management, multi-tenant indexing, or lifecycle policies.
- Familiarity with ClickHouse or other OLAP systems for analytics.
- Background in event-driven systems, data pipelines, or message brokers.
- Contributions to open-source or public technical writing on database performance or systems design.
EEO Statement:
The company is an Equal Opportunity Employer. As an employer subject to affirmative action regulations, we invite you to voluntarily provide the following demographic information. This information is used solely for compliance with government recordkeeping, reporting, and other legal requirements. Providing this information is voluntary and refusal to do so will not affect your application status. This data will be kept separate from your application and will not be used in the hiring decision.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Key skills/competency:
- Staff Backend Engineer
- Data Systems
- ElasticSearch
- MongoDB
- Firestore
- Redis
- Node.js
- TypeScript
- GCP
- Microservices
Skills & topics
- Staff Backend Engineer
- Backend Engineer
- Data Systems
- Database Architecture
- ElasticSearch
- MongoDB
- Firestore
- Node.js
- TypeScript
- GCP
- Microservices
- Scalability
- Reliability
- Observability
- Engineering Culture
How to get hired
- Tailor your resume: Highlight your 8+ years of backend experience, deep database expertise, and success with massive-scale data systems like ElasticSearch, MongoDB, or Firestore.
- Showcase your cloud skills: Emphasize your experience with GCP (GKE, Pub/Sub, Cloud Tasks) and observability tools (Grafana, Kibana, OpenTelemetry).
- Demonstrate leadership: Provide examples of how you've driven technical standards through RFCs, ADRs, and clear technical writing.
- Quantify your impact: Use numbers to illustrate your achievements in scaling systems, optimizing performance, and improving reliability.
- Prepare for technical deep dives: Be ready to discuss your approach to database architecture, query optimization, system design, and testing methodologies.
Technical preparation
Behavioral questions
Frequently asked questions
- What does a Staff Backend Engineer at HighLevel do in the Conversations team?
- As a Staff Backend Engineer on the Conversations team at HighLevel, you will be responsible for owning and evolving the data backbone that powers messaging at scale. This involves designing, operating, and scaling systems that handle billions of documents across various databases, ensuring reliability and performance.
- What specific technologies will I work with as a Staff Backend Engineer at HighLevel?
- You will work with a robust data stack including MongoDB, Firestore, Redis, ElasticSearch, and ClickHouse. The infrastructure is built on GCP, utilizing services like GKE, Pub/Sub, and Cloud Tasks. You'll be an expert in Node.js (TypeScript) for microservices development.
- Is this a hands-on role, or more focused on management?
- This is a hands-on Individual Contributor (IC) role. You will be actively coding, designing systems, conducting code reviews, and debugging production issues, while also guiding and mentoring other engineers on the team.
- What is the primary focus of the first project for this Staff Backend Engineer role?
- Your initial project will be to re-architect and scale ElasticSearch to efficiently handle billions of documents. This includes setting best practices for schema design, observability, and testing discipline across the organization.
- What kind of experience is required for the Staff Backend Engineer position at HighLevel?
- HighLevel requires 8+ years of backend engineering experience with deep database expertise, proven success with large-scale data systems like ElasticSearch, MongoDB, or Firestore, and strong skills in Node.js (TypeScript) and GCP.
- Does HighLevel use AI in its hiring process for the Staff Backend Engineer role?
- Yes, HighLevel may use AI tools to support parts of the hiring process, such as reviewing applications and analyzing resumes. However, these tools assist the recruitment team and do not replace human judgment; final hiring decisions are made by humans.
- What are the opportunities for mentorship and influence in this role?
- As a Staff Engineer, you will have significant opportunities to level up other engineers through constructive reviews and feedback. You will also influence the team's engineering culture by driving RFCs, ADRs, and design reviews, and by codifying repeatable engineering patterns.
- What does HighLevel mean by 'make our data systems boring'?
- The goal is to make the data systems predictable, fast, and easy to trust – essentially, to achieve a state of stable, reliable operation where they function seamlessly without causing disruptions or requiring constant, high-intensity attention from the engineering team.