Bengaluru, Karnataka, India · Hybrid
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 custo…
Skills: Backend architecture, Infrastructure engineering, Distributed systems, Machine learning infrastructure, GPU infrastructure
India · Remote OK
Are you passionate about the future of Artificial Intelligence and Natural Language Processing? Join us at Level AI, where we are on a mission to revolutionize the customer service industry. By leveraging the latest AI a…
Skills: Revenue Operations, Salesforce, Hubspot, Gong, Data Analysis
California, United States · On-site
Level AI is a fast-growing, AI-first Customer Experience Intelligence platform backed by top-tier investors and founded by leaders from Amazon, Google, and Meta. Role - We’re looking for a highly organized Operations Spe…
Skills: Executive Support, Business Operations, Calendar Management, Travel Coordination, KPI Tracking
United States · Remote OK
Level AI · Remote (US) · Reports to the CRO About Level AI Level AI is building the LLM-native platform for customer experience. We process 100% of contact center interactions in real time to power automated QA, real-tim…
Skills: Salesforce, Gong, Revenue Operations, Systems Design, GTM Strategy
United States · Remote OK
About Level AI Level AI is on a mission to turn every customer interaction into a strategic advantage. Our AI-native platform helps enterprises transform contact centers from cost centers into engines of customer intelli…
Skills: Backend Engineering, Distributed Systems, AI Agent Orchestration, LLMs, SLMs
India · Remote OK
About Level AI - Level AI is transforming how enterprises understand and engage with their customers. Our AI-native CX platform combines conversation intelligence, real-time agent guidance, and AI Virtual Agents to help …
Skills: AI Agent Deployment, API Integration, LLM Prompting, Workflow Design, Enterprise SaaS Integration
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You will lead the technical direction for backend and ML infrastructure, designing scalable systems for real-time data processing and model serving. You will also mentor senior engineers and drive architectural standards across the organization to support rapid growth.
Candidates must have 10+ years of experience building large-scale backend and infrastructure systems with a strong track record in architecture. A degree in Computer Science or equivalent is required, along with deep expertise in high-throughput systems and technical leadership.
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.
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.
\nWhat you'll doOwn 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.
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.
[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.
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.
Health coverage for you, your spouse, children, and parents.
Real ownership over systems used by enterprises worldwide, with the autonomy to decide how they're built.
[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.
The AI with the most customer experience.
Level AI pairs their proprietary AI stack with a unified quality, coaching, automation, and analytics layer. Every function learns from the same customer conversation data. Coaching plans reflect what QA scores surface, Product see the same friction patterns Operations sees, and the business comes together to deliver a unified, intelligent customer journey. Companies like Wayfair, Smartsheet, Chime, Gusto and SwissRe trust Level AI to deliver efficient, high-quality, customer experiences while elevating customer strategy.
Offices: 444 Castro St, Suite 305, Mountain View, California 94041, US · New Delhi, Delhi 110055, IN
The AI with the most customer experience.
Level AI pairs their proprietary AI stack with a unified quality, coaching, automation, and analytics layer. Every function learns from the same customer conversation data. Coaching plans reflect what QA scores surface, Product see the same friction patterns Operations sees, and the business comes together to deliver a unified, intelligent customer journey. Companies like Wayfair, Smartsheet, Chime, Gusto and SwissRe trust Level AI to deliver efficient, high-quality, customer experiences while elevating customer strategy.
Offices: 444 Castro St, Suite 305, Mountain View, California 94041, US · New Delhi, Delhi 110055, IN
