Design, build, and optimize enterprise-grade agentic and multi-agent systems using modern AI orchestration frameworks and tools.
Drive integration standards for AI applications through Model Context Protocol (MCP), external tools, model routing frameworks, and enterprise data systems.
Transform research prototypes and proof-of-concepts into scalable, secure, reproducible, and production-ready AI applications.
Optimize model inference infrastructure through quantization strategies, runtime tuning, memory optimization, dynamic batching, and efficient serving architectures.
Design and support distributed AI workloads across Kubernetes-based environments and GPU-enabled infrastructure.
Implement observability, monitoring, context management, caching strategies, and performance guardrails that enhance system reliability and user experience.
Establish and enforce engineering best practices for code quality, automated testing, security compliance, and production readiness.
Conduct deep technical design and code reviews, providing architectural guidance and validating technical trade-offs before deployment.
Mentor software engineers, machine learning engineers, and technical teams through thought leadership and AI engineering best practices.
What you’ll need to be successful.
Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, Electrical Engineering, Applied Mathematics, or a related quantitative discipline.
10-15 years of hands-on experience in software engineering, systems architecture, distributed systems, or enterprise backend development.
5+ years of experience developing, deploying, and operating production machine learning systems, with significant recent experience in Generative AI technologies.
Demonstrated success serving as a technical lead, architect, or principal engineer for high-scale, highly available enterprise platforms.
Expert-level proficiency in Python and modern software engineering patterns, including concurrency, distributed computing, performance tuning, and system optimization.
Deep expertise with Kubernetes, containerized workloads, distributed systems, and GPU infrastructure management across enterprise environments.
Hands-on experience deploying and optimizing model serving platforms such as Triton Inference Server, vLLM, TGI, or similar inference technologies.
Advanced experience with AI orchestration frameworks including LangChain, LangGraph, LlamaIndex, AutoGen, or related technologies.
Strong understanding of MLOps tooling, experiment tracking, model registries, and lifecycle management solutions such as MLflow and Weights & Biases.
Experience implementing AI solutions across text, image, video, speech, audio, or multimodal domains is considered an asset.
Proven ability to communicate complex technical decisions, performance trade-offs, and architectural recommendations to both technical and business stakeholders.
Strong execution mindset with a focus on operational excellence, scalability, performance, and business impact.
About the team.
The AI Engineering team is responsible for building and scaling enterprise AI capabilities that enable innovation across McCain’s business functions. As a Principal AI Engineer, you will serve as a senior technical leader and trusted advisor across engineering teams, partnering closely with AI engineers, software developers, platform engineers, infrastructure teams, data professionals, and business stakeholders.
This role is positioned at the center of McCain’s AI technology strategy, helping establish technical standards, accelerate delivery, and ensure that advanced AI capabilities are built with reliability, scalability, security, and long-term value in mind.
About McCain.
Click Here to learn more about McCain and how we provide opportunities to make an impact that matters.
Leadership principles.
At McCain, our leadership principles guide how we engage with customers, collaborate as a team, and achieve success. We focus on understanding customer needs, driving innovation, empowering people, and taking ownership to clear obstacles and deliver results.
AI & Digital Capabilities.
At McCain, AI and digital capabilities are part of how we work and innovate. We value curiosity toward emerging technologies and the thoughtful, responsible use of AI-enabled tools to improve outcomes as part of our future-ready culture.
The McCain experience.
We are McCain. This statement is a testament to our collective strength and our individual value. Your contributions play a vital role in our success. Our winning culture is rooted in authenticity and trust, empowering us to bring out the best in one another. Here, you’ll find opportunities to learn, grow, and thrive. Join us and experience why we’re better together.
McCain Foods is an equal opportunity employer. As a global family-owned company, we strive to be the employer of choice in the diverse communities around the world in which we live and work. We recognize that inclusion drives our creativity, resilience, and success and makes our business stronger. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, age, veteran status, disability, or any other protected characteristic under applicable law.
McCain is an accessible employer. If you require an accommodation throughout the recruitment process (including alternate formats of materials or accessible meeting rooms), please let us know and we will work with you to find appropriate solutions.
Your privacy is important to us. By submitting personal data or information to us, you agree this will be handled in accordance with McCain’s Global Privacy Policy and Global Employee Privacy Policy, as applicable. McCain leverages AI in the hiring process, though all final decisions are made by humans. You can understand our approach to AI and how your personal information is being handled here.
Job Family: Information Technology
Location(s): IN - India : Haryana : Gurgaon
Company: McCain Foods(India) P Ltd
