Engineering Leader - Applied AI

DevRev; Bengaluru; On-site; INR 3,800,000 - 7,000,000; Full time

Job summary

DevRev seeks an engineering and customer-facing leader to own end-to-end AI-driven business transformation projects, shaping architecture and delivery for customers. You will work with pre-sales to scope integrations and drive post-sales deployments, building proofs-of-concept and scalable solutions on the DevRev platform.

You bring 5+ years in software design/AI, strong leadership, and hands-on cloud/DevOps experience to influence outcomes and drive customer success.

Qualifications

• 5+ years in software design and development, AI/ML engineering, or technical consulting with customer-facing experience.
• Proven ability to lead technology teams as a hands-on leader.
• Strong written and verbal communication to articulate technical concepts.

Responsibilities

• Own end-to-end design and delivery of AI-driven business transformation projects.
• Lead execution: define plans, align teams, and ensure timely deployments.
• Design & deploy AI agents using connectors, workflows, and AI on DevRev platform.
• Integrate systems with APIs, webhooks, and data pipelines.
• Tune prompts, logic, and configurations for reliability and scalability.
• Prototype and iterate through live demos and proofs-of-concept.
• Advise customers on AI agent architecture and long-term scalability.

Skills

Customer-facing

Leadership

AI/ML engineering

Communication

Cloud & DevOps

System Integration

Data-Driven Mindset

Software design

Education

Bachelor's degree in Computer Science or Engineering

Master's degree in a related field

Tools

AWS

GCP

Azure

CI/CD

Containers

Observability

Job description

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

• 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

Applied AI Knowledge: Large language models (LLMs), prompt engineering, frameworks like RAG and function calling, and building evals to validate agentic AI solutions.