---
title: 'Senior Backend Engineer - Analytics, Noida at Level AI'
canonical: 'https://feeny.ai/job/senior-backend-engineer-analytics-noida-level-ai-noida-x5wprabhjwy4'
type: 'job'
last_seen: '2026-09-07'
---

# Senior Backend Engineer - Analytics, Noida at Level AI

- **Company:** Level AI
- **Location:** Noida, India
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2025-08-20
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.lever.co/levelai/6d4ce92d-88d9-4d78-b30d-ae22b12a268f

## Job description

Level AI was founded in 2019 and is a Series C startup headquartered in Mountain View, California. Level AI revolutionises customer engagement by transforming contact centres into strategic assets. Our AI-native platform leverages advanced technologies such as Large Language Models to extract deep insights from customer interactions. By providing actionable intelligence, Level AI empowers organisations to enhance customer experience and drive growth. Consistently updated with the latest AI innovations, Level AI stands as the most adaptive and forward-thinking solution in the industry.

Competencies:

Data Modelling: Skilled in designing data warehouse schemas (e.g., star and snowflake schemas), with experience in fact and dimension tables, as well as normalization and denormalization techniques. Data Warehousing & Storage Solutions: Proficient with platforms such as Snowflake, Amazon Redshift, Google BigQuery, and Azure Synapse Analytics. ETL/ELT Processes: Expertise in ETL/ELT tools (e.g., Apache NiFi, Apache Airflow, Informatica, Talend, dbt) to facilitate data movement from source systems to the data warehouse. SQL Proficiency: Advanced SQL skills for complex queries, indexing, and performance tuning. Programming Skills: Strong in Python or Java for building custom data pipelines and handling advanced data transformations. Data Integration: Experience with real-time data integration tools like Apache Kafka, Apache Spark, AWS Glue, Fivetran, and Stitch. Data Pipeline Management: Familiar with workflow automation tools (e.g., Apache Airflow, Luigi) to orchestrate and monitor data pipelines. APIs and Data Feeds: Knowledgeable in API-based integrations, especially for aggregating data from distributed sources.

## Responsibilities -

- Design and implement analytical platforms that provide insightful dashboards to customers.
- Develop and maintain data warehouse schemas, such as star schemas, fact tables, and dimensions, to support efficient querying and data access.
- Oversee data propagation processes from source databases to warehouse-specific databases/tools, ensuring data accuracy, reliability, and timeliness.
- Ensure the architectural design is extensible and scalable to adapt to future needs.

Requirement -

- Qualification: B.E/B.Tech/M.E/M.Tech/PhD from tier 1 Engineering institutes with relevant work experience with a top technology company.
- 3+ years of Backend and Infrastructure Experience with a strong track record in development, architecture and design.
- Hands-on experience with large-scale databases, high-scale messaging systems and real-time Job Queues.
- Experience navigating and understanding large scale systems and complex code-bases, and architectural patterns.
- Proven experience in building high-scale data platforms.
- Strong expertise in data warehouse schema design (star schema, fact tables, dimensions).
- Experience with data movement, transformation, and integration tools for data propagation across systems.
- Ability to evaluate and implement best practices in data architecture for scalable solutions.

Nice to have:

- Experience with Google Cloud, Django, Postgres, Celery, Redis.
- Some experience with AI Infrastructure and Operations.

To learn more visit : https://thelevel.ai/ Funding : https://www.crunchbase.com/organization/level-ai LinkedIn : https://www.linkedin.com/company/level-ai/ Our AI platform : https://www.youtube.com/watch?v=g06q2V_kb-s

## About Level AI

## Company Overview
- **One-liner**: Level AI is a customer experience platform that scores every customer interaction, deploys AI voice agents, and turns conversations into actionable insights for enterprise contact centers.
- **Entity Type**: Private (Series C, $74.4M total funding)
- **Headquarters**: Mountain View, California, United States (with an office in New Delhi, India)
- **Founded**: 2018
- **Founders**: Not publicly available

## Core Business
- **Primary industry**: Customer Experience (CX) Platform / AI-Powered Contact Center Software
- **Target customers**: B2B, Enterprise (Fortune 500 healthcare, financial services, and retail environments)
- **Mission or purpose statement**: To help enterprise contact centers automate quality management, assist and coach agents, and understand the voice of the customer at 100% coverage.

## Products & Services
- **Quality Management**: Scores 100% of conversations across channels to standardize quality at scale.
- **AI Virtual Agents**: Deploys AI voice agents for triage to resolution, automating complex workflows.
- **Voice of the Customer**: Extracts insights from every interaction to inform product, operations, and strategy.
- **Assist**: Provides real-time AI or manager help to agents during calls.
- **Analytics 360**: Delivers customer and team intelligence dashboards.
- **Screen Recording**: Monitors agents in real time.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Annual Revenue of $15M (LinkedIn estimate); Total Funding of $74.4M
- **Notable Investors/Partners**: Battery Ventures (led Series A & B), Eniac Ventures (led Seed), Adams Street Partners (led Series C). Customers include Wayfair, Smartsheet, Chime, Gusto, and SwissRe.
- **Growth Signals**: 162 employees (+8.8% YoY); processes 4 trillion tokens and analyzes 1 billion+ customer interactions per year; serves enterprises with a combined $500B in market cap; LinkedIn followers grew +40.1% in the last year.

## Competitive Advantages
- **Proprietary AI Architecture**: Uses seven task-specific models for customer experience that are up to 49x more cost-efficient, 4x faster, and with accuracy on par with frontier LLMs.
- **Unified Intelligence Layer**: Every function (QA, coaching, automation, analytics) learns from the same customer conversation data, creating a continuous improvement loop.
- **Enterprise-Grade Compliance**: ISO 27001, HIPAA, SOC2, PCI, and GDPR certified.
- **High Product Satisfaction**: 4.8/5.0 product rating (199 reviews).

## Strategic Focus
- **Deepening Enterprise Penetration**: Targeting high-volume, high-stakes customer operations in regulated industries (healthcare, financial services, retail).
- **AI Model Development**: Continuing to build and refine domain-specific models rather than relying on general-purpose LLM wrappers.
- **Global Expansion**: Growing engineering presence in India (Noida, Bangalore) while maintaining US headquarters.

## Why Work Here
- **Impact & Ownership**: Employees take on big projects single-handedly and make a direct impact. The company "ships fast and owns the outcome."
- **Cutting-Edge AI Work**: Engineers work on state-of-the-art NLP, speech, and machine learning problems at scale (4 trillion tokens processed per year).
- **Growth Culture**: Described as "learning and growing…fast," with a focus on hiring exceptional talent.
- **Remote/Hybrid Policy**: Some roles are listed as remote (e.g., Senior Backend Engineer - AI Agents), while others are on-site (Bay Area, California, or Noida/Bangalore, India).
- **Compensation & Culture**: Employer rating of 3.8/5.0 (98 reviews), with work-life balance at 3.5, compensation at 3.6, and culture at 3.5.
- **Open Roles**: Focus on senior engineering positions (ML, NLP, Backend, SRE) and finance.

## Sources
1. [thelevel.ai](https://thelevel.ai)
2. [thelevel.ai/careers](https://thelevel.ai/careers)
3. [thelevel.ai/about-us](https://thelevel.ai/about-us)
4. [linkedin.com/company/level-ai](https://www.linkedin.com/company/level-ai)
5. [jobs.lever.co/levelai](https://jobs.lever.co/levelai)

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