Role Summary

Company: TrueFoundry

Location: Bengaluru, India

Type: Internship

About TrueFoundry

TrueFoundry is building the infrastructure layer powering the next generation of AI applications. As enterprises move beyond simple chatbots to production-grade AI agents, they need scalable infrastructure for model routing, agent orchestration, governance, security, and compute management.

Backed by Sequoia Capital and Intel Capital, TrueFoundry serves leading organizations including CVS, Mastercard, Siemens, Paytm, Synopsys, and Zscaler, helping them deploy and manage AI systems at scale.

The company offers a cloud-native platform that enables organizations to build, deploy, fine-tune, and manage ML and GenAI applications faster, more efficiently, and with enterprise-grade governance controls.

About the Role

As a Backend Engineering Intern, you'll work directly with the engineering team to build the infrastructure powering large-scale AI and machine learning systems. You'll contribute to core platform components, developer tooling, APIs, integrations, and distributed systems that help enterprises deploy production AI workloads.

This role is ideal for candidates passionate about backend engineering, cloud infrastructure, distributed systems, Kubernetes, and AI platforms.

Roles & Responsibilities

Backend Development

• Design and develop scalable backend services using Python.
• Build and maintain high-performance APIs using REST and gRPC.
• Develop reliable and maintainable software following engineering best practices.
• Work with Protobufs, Thrift, and modern communication protocols.

AI Infrastructure & Platform Engineering

• Contribute to systems that enable deployment and management of ML and LLM applications.
• Help build infrastructure for model serving, orchestration, governance, and observability.
• Work on components supporting AI Gateway and AI Deploy products.

Platform Integrations

• Build integrations with third-party platforms and developer tools.
• Enable seamless adoption of TrueFoundry within customer workflows.
• Develop APIs and services that interact with AI, cloud, and infrastructure platforms.

Distributed Systems & Cloud Technologies

• Work on distributed and concurrent systems powering enterprise AI workloads.
• Contribute to cloud-native services running on Kubernetes.
• Assist in building scalable and fault-tolerant backend architectures.

Database & Data Engineering

• Work with relational and non-relational databases.
• Design efficient data access patterns and optimize system performance.
• Support data-intensive workloads and platform services.

Engineering Excellence

• Participate in code reviews, architecture discussions, and technical design sessions.
• Write clean, testable, and production-ready code.
• Contribute to open-source projects and internal developer tooling.

Eligibility Criteria

Required Skills

• Strong proficiency in Python programming.
• Solid understanding of Data Structures, Algorithms, and Object-Oriented Programming.
• Strong problem-solving and analytical skills.
• Knowledge of REST APIs and backend system design.
• Familiarity with databases and query optimization.
• Ability to work independently and take ownership of projects.

Preferred Skills

• Experience building concurrent or distributed systems.
• Familiarity with Kubernetes, Docker, AWS, or cloud-native technologies.
• Knowledge of gRPC, Protobufs, Thrift, or similar frameworks.
• Experience with relational and non-relational databases.
• Understanding of software architecture and scalable backend systems.
• Contributions to open-source projects.
• Prior exposure to Machine Learning, MLOps, LLMOps, or AI platforms.

Educational Background

• Pursuing or recently completed a degree in Computer Science, Engineering, or a related field.
• Strong preference for candidates from top engineering institutions.
• Exceptional candidates with strong project or open-source experience are encouraged to apply.

What We're Looking For

• Strong ownership mindset and execution ability.
• Curiosity and willingness to solve challenging technical problems.
• Ability to thrive in fast-paced startup environments.
• Data-driven decision making and analytical thinking.
• Comfort working with ambiguity and rapidly evolving technologies.
• Strong communication and collaboration skills.
• Passion for building infrastructure that powers real-world AI systems.

What You'll Gain

• Opportunity to work on cutting-edge AI infrastructure and LLMOps platforms.
• Hands-on experience with Kubernetes, distributed systems, cloud technologies, and backend engineering.
• Exposure to production-scale AI deployments used by leading global enterprises.
• Mentorship from experienced engineers and startup leaders.
• Experience building products at the intersection of AI, cloud infrastructure, and developer platforms.
• Opportunity to contribute to systems shaping the future of enterprise AI.