Engineering Leader - Applied AI | DevRev · Teeming.ai
DevRev
AI is changing the way we work. At DevRev, we’re making it conversational.
DevRev’s AI-native business operating system designed for you to experience conversational AI at work—transforming complex…
AI is changing the way we work. At DevRev, we’re making it conversational.
DevRev’s AI-native business operating system designed for you to experience conversational AI at work—transforming complex…
Core product: Computer — AI-native work platform / dev-centric CRM with shared memory
Latest reported funding: $100.8M (Series A)
Reported valuation: $1.15–1.2B
Company Overview
Problem Domain
Bridging developer/product/support workflows and customer data using AI to improve productivity and customer-centric operations.
Founded
2020
Industry
Software Development
Funding Track Record
Seed- July 2021
$50,000,000
Company launched from stealth with a $50M seed round.
Series A- 2024
$100,800,000
Company statement describing completion of a ~$100.8M Series A and valuation reported around $1.1–1.2B.
Investor Signal
“Backed by prominent venture investors including Khosla Ventures and Mayfield Fund”
Founders
What we do
Join the Team
Engineering Leader - Applied AI
HybridBengaluru, Karnataka, IN
Hybrid • Bengaluru, Karnataka, IN
About the role
As an Engineering and Customer facing leader, you will own the end-to-end design and delivery of AI-driven business transformation projects, while also innovating on tools and services on the DevRev product. You'll work closely with pre-sales teams to scope technical integration and implementation strategies, translating business requirements into architectural solutions. Once opportunities move to post-sales, your team will own the detailed technical designs from original scoping documents and drive execution to build proofs-of-concept, custom integrations, and solutions that validate technical feasibility.
What you'll do
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Customer-facing:
Working directly with customers
Lead Execution
: Define project plans, align internal teams, and ensure timely delivery of deployments
Design & Deploy AI Agents:
Build and configure intelligent solutions leveraging snap-ins, connectors (AirSync), workflows, and AI agents on the DevRev platform to solve real customer problems.
Integrate Systems
: Connect AI agents with external platforms (e.g., CRMs, APIs, databases) for seamless workflow automation.
Optimize Performance
: Tune prompts, logic, and agent configurations for accuracy, reliability, and scalability.
Own Requirements
: Partner with customers to deeply understand their needs and translate them into technical agent specifications.
Prototype & Iterate
: Lead live demos, build rapid proof-of-concepts, and refine solutions through customer feedback.
Advise Customers
: Act as a trusted technical advisor on AI agent architecture, performance, and long-term scalability.
What you'll bring
Experience
: 5+ years in software design and development, AI/ML engineering, or technical consulting coupled with customer-facing experience
Leadership:
3+ years leading technology teams as a hands-on leader
Customer Empathy
: A bias for action and a relentless focus on solving problems for customers.
Communication
: Strong written and verbal skills to articulate technical concepts to both engineers and business stakeholders.
Cloud & DevOps
: Hands-on experience with AWS, GCP, or Azure, and modern DevOps practices (CI/CD, containers, observability).
System Integration
: Comfortable integrating systems via APIs, webhooks, and event/data pipelines.
Data-Driven Mindset
: Use A/B testing, telemetry, and metrics to guide decisions and drive improvements.
Background
: Bachelor's or Master’s degree in Computer Science, Engineering, or related discipline. Advanced degrees or certifications in AI/architecture frameworks (e.g., TOGAF, SAFe) are a plus
Nice to have
Coding Skills:
Strong proficiency using TypeScript/JavaScript, Python, data structures and algorithms, (Nice to have: Go)
Applied AI Knowledge:
Large language models (LLMs), prompt engineering, frameworks like RAG and function calling, and building evals to validate agentic AI solutions.
