Project Role : Large Language Model Architect
Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.
Must have skills : Machine Learning (ML)
Good to have skills : NA
Minimum 18 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary:
We are seeking an experienced Engineering Manager to lead the delivery and technical execution of three strategic engineering Context & Ontology, Agent Runtime, and platform DevOps. This role is responsible for leading a high-performing team of approximately 17 engineers, driving engineering excellence, and ensuring the successful delivery of the core platform capabilities that power enterprise AI solutions.
As an Engineering Manager, you will be responsible for building strong engineering teams, establishing technical and operational best practices, mentoring engineering leaders, and partnering closely with Architects, Product Managers, and senior leadership to deliver secure, scalable, and reliable platform capabilities. This role requires a balance of technical leadership, people management, delivery ownership, and strategic planning.

Roles & Responsibilities:

- Lead and manage the engineering delivery for Context & Ontology, Agent Runtime) and Platform DevOps, ensuring successful execution of platform initiatives aligned with business priorities.
- Provide technical leadership by setting engineering standards, conducting architecture and design reviews, and guiding teams on complex technical decisions.
- Partner closely with the Lead Architect to drive cross-functional architectural alignment and resolve technical challenges across engineering pods.
- Own engineering delivery, including project planning,



execution, risk management, resource allocation, and timely delivery of high-quality platform capabilities.
- Build, mentor, and develop high-performing engineering teams by providing coaching, career development, performance management, and technical guidance.
- Lead end-to-end hiring activities for engineering roles within the assigned pods, including technical interviews, candidate evaluations, and workforce planning.
- Establish and continuously improve engineering best practices, including 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 to ensure high platform availability.
- Monitor engineering metrics, delivery progress, platform quality, and team health, proactively identifying risks and driving mitigation plans.
- Collaborate with Product Management, Platform Engineering, Security, and DevOps teams to ensure successful delivery of scalable and secure enterprise platform solutions.
- Drive continuous improvement initiatives focused on engineering productivity, automation, developer experience, and operational efficiency.
- Provide regular updates to senior leadership on engineering health, delivery status, hiring progress, technical risks, and capability development.

Professional & Technical Skills:

- 12–15 years of experience in software engineering,



with significant experience leading engineering teams delivering large-scale enterprise platforms or cloud-native applications.
- 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.
- Robust 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 engineering best practices, including 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.
- Familiarity with AI platforms, Agentic AI, Knowledge Graphs, Platform Engineering, DevOps, and enterprise-scale distributed systems is highly desirable.
- 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.

Additional Information:

- Experience need 12–15 years
- Role Engineering Manager – Platform Engineering
- Team Size Approximately 17 Engineers across Context & Ontology, Agent Runtime, and Platform DevOps.

15 years full time education

📌 Large Language Model Architect (India)
🏢 Accenture
📍 India