Level AI

Optimizes call center data with AI

Forward Deployed Engineer - Agents, Remote

Implementation & Technical Account ManagementConfirmed live in the last 24 hours

Full-timeRemote in IndiaNo salary listedRemote

About the Job

Requirements

5+ years in a technical customer-facing role (Solutions Engineering, Forward Deployed Engineering, Implementation Engineering, Technical Consulting, Technical PM, or similar)
Strong technical foundation - comfortable coding, working with APIs, and building integrations end-to-end
Experience delivering production-grade enterprise solutions requiring testing, validation, and iteration
Ability to communicate with senior technical stakeholders and translate requirements into execution plans
Comfortable operating in fast-moving, ambiguous environments
Comfortable working in EST hours(3:30 AM IST)

Responsibilities

Own end-to-end execution of AI agent deployments from discovery and scoping through launch and optimization.
Configure agent workflows, decision logic, and automation behaviors to maximize accuracy, reliability, and business outcomes.
Implement guardrails and validation frameworks to ensure safe, compliant, and predictable agent performance.
Build, test, and validate integrations with enterprise systems (e.g., CRM, ticketing, telephony, data platforms).
Partner with customer technical stakeholders to define success criteria, gather requirements, and deliver against timelines.
Translate customer needs into clear implementation plans and documentation.
Run tight feedback loops with Engineering and Product to improve platform capabilities.
Collaborate with Product, Engineering, Design, and GTM teams to deliver repeatable, best-in-class deployments.

Desired Qualifications

Experience building with LLMs or AI agents (prompting, evaluation, guardrails, workflow design).
Experience integrating enterprise SaaS systems (CRM, ticketing, data pipelines) with attention to security and compliance.
Computer Science, Engineering, or Math degree (or equivalent experience).
Strong product instincts - ability to define success metrics and contribute customer insights to product evolution.

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 brands deliver exceptional customer experiences at scale.Leading enterprises use Level AI to automate routine interactions, coach agents in real time, and unlock insights from customer conversations across voice, chat, email, and messaging channels.Backed by Battery Ventures, ENIAC, and leading AI operators from Amazon Alexa, Google, and Meta, we are building the future of customer experience powered by agentic AI and specialized language models (SLMs).At Level AI, we operate with urgency, ownership, and a deep customer-first mindset. We value builders who move fast, think clearly, and obsess over delivering measurable impact for customers.

About the Role - As a Forward Deployed Engineer - Agents, you will lead the end-to-end implementation of AI Virtual Agents and CX automation workflows for customers.This is a highly technical, customer-facing role where you will translate business requirements into production-ready agent deployments that drive measurable impact — including containment, resolution speed, customer satisfaction, and operational efficiency.You will partner with customers and internal teams to define success, execute builds, and influence the evolution of Level AI’s agentic platform based on real-world needs.This role is ideal for someone who thrives in fast-moving environments, enjoys shipping customer-facing technical solutions, and balances hands-on execution with structured problem-solving.

In This Role, You Will -

- Own end-to-end execution of AI agent deployments from discovery and scoping through launch and optimization.

- Configure agent workflows, decision logic, and automation behaviors to maximize accuracy, reliability, and business outcomes.

- Implement guardrails and validation frameworks to ensure safe, compliant, and predictable agent performance.

- Build, test, and validate integrations with enterprise systems (e.g., CRM, ticketing, telephony, data platforms).

- Partner with customer technical stakeholders to define success criteria, gather requirements, and deliver against timelines.

- Translate customer needs into clear implementation plans and documentation.

- Run tight feedback loops with Engineering and Product to improve platform capabilities.

- Collaborate with Product, Engineering, Design, and GTM teams to deliver repeatable, best-in-class deployments.

Your Background Looks Something Like This -

- 5+ years in a technical customer-facing role (Solutions Engineering, Forward Deployed Engineering, Implementation Engineering, Technical Consulting, Technical PM, or similar).

- Strong technical foundation - comfortable coding, working with APIs, and building integrations end-to-end.

- Experience delivering production-grade enterprise solutions requiring testing, validation, and iteration.

- Ability to communicate with senior technical stakeholders and translate requirements into execution plans.

- Comfortable operating in fast-moving, ambiguous environments.

- Confortable working in EST hours(3:30 AM IST)

Even Better If You Have -

- Experience building with LLMs or AI agents (prompting, evaluation, guardrails, workflow design).

- Experience integrating enterprise SaaS systems (CRM, ticketing, data pipelines) with attention to security and compliance.

- Computer Science, Engineering, or Math degree (or equivalent experience).

- Strong product instincts - ability to define success metrics and contribute customer insights to product evolution.

About the Company

Level AI

Optimizes call center data with AI

Level AI provides software that improves customer experience and operational efficiency in the BPO sector by integrating human and machine intelligence. Its platform unifies call center data from multiple sources and uses intelligent automation and machine learning to automate tasks, guide decisions, and improve interactions, all delivered through a subscription model. It differentiates itself by offering end-to-end data integration across silos and blending human expertise with ML to boost sales conversions and QA productivity in call centers. The goal is to help BPO providers deliver better customer experiences while making operations more efficient and cost-effective.

Company size: 201-500
Company stage: Acquired
Total funding: $74.4M
Headquarters: Mountain View, CA
Founded: 2018

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