Large Language Model Architect

Overview

Lead the delivery and technical execution of the Context & Ontology, Agent Runtime, and Platform DevOps engineering areas. Build high-performing engineering teams and deliver secure, scalable, and reliable platform capabilities for enterprise AI solutions.

What you'll do

• Lead and manage engineering delivery for Context & Ontology, Agent Runtime, and Platform DevOps initiatives aligned with business priorities.
• Set engineering standards, conduct architecture and design reviews, and guide teams on complex technical decisions.
• Partner with the Lead Architect to drive cross-functional architectural alignment and resolve technical challenges across engineering pods.
• Own project planning, execution, risk management, resource allocation, and timely delivery of high-quality platform capabilities.
• Build, mentor, and develop high-performing engineering teams through coaching, career development, performance management, and technical guidance.
• Lead hiring activities, including technical interviews, candidate evaluations, and workforce planning.
• Establish and improve coding standards, code reviews, testing strategies, CI/CD pipelines, release management, and operational excellence.
• Define and manage incident response processes, production support models, platform reliability, and on-call rotations.
• Monitor engineering metrics, delivery progress, platform quality, and team health, identifying risks and driving mitigation plans.
• Collaborate with Product Management, Platform Engineering, Security, and DevOps teams to deliver scalable and secure enterprise platform solutions.
• Drive continuous improvement in engineering productivity, automation, developer experience, and operational efficiency.
• Provide senior leadership updates on engineering health, delivery status, hiring progress, technical risks, and capability development.

What you'll need

• 12–15 years of experience in software engineering, with significant experience leading engineering teams delivering large-scale enterprise platforms or cloud-native applications.
• Machine Learning (ML) skills.
• Proven experience managing multiple engineering teams or cross-functional technology organizations in Agile environments.
• Strong technical background in distributed systems, microservices architecture, cloud-native application development, DevOps practices, and enterprise software engineering.
• Experience driving architecture reviews, engineering governance, technical decision-making, and software quality initiatives.
• Strong understanding of software development lifecycle (SDLC), CI/CD pipelines, release management, production operations, and incident management.
• Experience leading hiring, mentoring, performance management, and career development for software engineering teams.
• Excellent knowledge of secure coding, code quality, testing automation, observability, and operational excellence.
• Strong understanding of cloud platforms such as Azure, AWS, or Google Cloud, along with container technologies including Docker and Kubernetes.
• Excellent communication, stakeholder management, conflict resolution, and organizational leadership skills.
• Ability to manage competing priorities, influence cross-functional teams, and deliver results in a fast-paced enterprise environment.
• 15 years full time education.

Nice to have

• Familiarity with AI platforms, Agentic AI, Knowledge Graphs, Platform Engineering, DevOps, and enterprise-scale distributed systems is highly desirable.

Details

• Location: Bengaluru.
• Role: Engineering Manager – Platform Engineering.
• Team size: Approximately 17 engineers across Context & Ontology, Agent Runtime, and Platform DevOps.
• The role includes on-call rotations.