---
title: 'Principal Software Engineer — Backend & Infrastructure - Noida / Bengaluru at Level AI'
canonical: 'https://feeny.ai/job/principal-software-engineer-backend-infrastructure-noida-bengaluru-level-ai-7htvh3ph2tw6'
type: 'job'
last_seen: '2026-09-07'
---

# Principal Software Engineer — Backend & Infrastructure - Noida / Bengaluru at Level AI

- **Company:** Level AI
- **Location:** Noida, India
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-08-10
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.lever.co/levelai/d9c3409d-a86f-4901-b628-d27813c673b6

## Job description

## About Level AI

Level AI is a Series C conversational intelligence company headquartered in Mountain View, CA, backed by top-tier VCs and Silicon Valley operators. We help enterprise contact centers understand every customer conversation — using speech AI, NLP/NLU, and retrieval systems to turn millions of unstructured interactions into decisions businesses can act on.

## Why this role exists

We're at the scaling inflection point. The systems that carried us from Series A to Series C won't carry us to the next stage, and we need someone to own that transition — not just build inside it. This is a Principal role: you'll set technical direction for backend and ML infrastructure across multiple teams, make the architectural calls that are expensive to reverse, and raise the engineering bar through design reviews, mentorship, and the standards you set by example. You'll report to the VP of Engineering and partner directly with our ML, Product, and Infrastructure leads across both sites. You'll work alongside engineers from Amazon, Google, and Meta who chose to build here because the problems are unsolved and the ownership is real.

## What you'll do

- Own the architecture for real-time data processing at scale. Design and evolve distributed messaging systems that handle high-throughput streaming workloads with strict latency requirements.

- Build the ML platform that lets us ship models faster. Define and execute the technical roadmap for training and serving infrastructure as our models grow in size, complexity, and inference cost.

- Scale our GPU infrastructure. Own capacity planning, scheduling, and utilization across training and inference fleets — deciding what runs where, how we handle burst demand, and how we keep spend tied to actual throughput rather than idle reservations.

- Scale inference. Drive down latency and cost per request as model complexity and traffic grow: batching and routing strategies, quantization and compilation, autoscaling, and caching — without degrading output quality.

- Make reliability a property of the system, not a heroic effort. Drive uptime, observability, and incident response for serving systems that enterprise customers depend on in production.

- Turn ambiguous business problems into executable technical plans. Partner with Product and GTM to scope large cross-functional initiatives, then break them into work other teams can run with.

- Multiply the team. Lead design reviews, mentor senior engineers, and shape the engineering practices that outlast any single project.

- Bring the outside in. Evaluate emerging tools and techniques with judgment — adopt what earns its complexity, skip what doesn't.

What success looks like in your first year

- 90 days: You've mapped our critical paths and failure modes, shipped a meaningful improvement to a serving or pipeline bottleneck, and earned trust across both sites.

- 6 months: You own a published technical roadmap for [messaging / ML infra], with at least one major migration or redesign underway. GPU utilization and inference cost per request are measured, and trending the right way.

- 12 months: Our infrastructure scales predictably with customer growth, inference cost stays flat or falls as volume rises, on-call load is down, and other engineers are making better architectural decisions because of standards you established.

## What you'll bring

- [10]+ years building backend and infrastructure systems, with a track record of owning architecture and design at scale — not just implementing it.

- Deep, hands-on experience with large-scale databases, high-throughput messaging systems, and real-time job queues.

- Proven ability to navigate large, complex codebases and reason clearly about architectural tradeoffs in systems you didn't build.

- Experience mentoring senior engineers and driving technical decisions through influence rather than authority.

- Strong written communication — you'll be making technical cases to engineers in two time zones and business cases to executives.

- BTech/MTech/PhD in Computer Science or equivalent. At this level we weight track record well above pedigree.

Bonus points for

- Production experience with our stack: Django, Celery, Redis, PostgreSQL, and Google Cloud.

- Hands-on experience scaling GPU infrastructure and model inference in production — capacity planning, scheduling and utilization, autoscaling, and latency/cost optimization under real traffic.

- Depth in specific inference tooling — vLLM, TensorRT, Triton, Ray Serve, or equivalents — and experience benchmarking tradeoffs between them.

- Experience scaling a platform through a comparable growth stage (Series C → D, or equivalent), especially at a global product company's India site.

- Background in speech, NLP, or information retrieval systems.

## Compensation & benefits

- Health coverage for you, your spouse, children, and parents.

- [home-office and connectivity allowance / annual learning budget / parental leave — trim to what's accurate].

- Real ownership over systems used by enterprises worldwide, with the autonomy to decide how they're built.

## How we hire

[4] stages, typically [2] weeks end to end: recruiter screen → technical deep dive → system design → team and leadership conversations → offer. Interviews are conducted from our India team with [one/two] conversations with US-based leadership. We'll tell you where you stand at every step.

Level AI is an equal opportunity employer. We hire and promote on merit and evaluate all applicants without regard to caste, religion, sex, gender identity, sexual orientation, marital or parental status, disability, or any other personal characteristic unrelated to the job. We maintain a zero-tolerance policy on harassment in line with the POSH Act, 2013. If you need any accommodation during the interview process, tell us — we'll arrange it.

## 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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