LLM Integration Engineer

Company Description People Foundry is a recruitment and staffing company dedicated to aligning business vision with the right talent. The organization focuses on understanding the needs behind every hire, the potential behind every profile, and the ambitions driving each growing team. Rather than simply filling vacancies, People Foundry creates meaningful connections between business requirements and human capability. This approach helps organizations build strong teams that move their business forward. People Foundry is committed to enabling growth by shaping teams that support long-term success.
Role Description The LLM Integration Engineer is a full-time, on-site role based in Delhi, India. This position is responsible for designing, developing, and integrating Large Language Model (LLM) capabilities into existing and new software systems. Day-to-day tasks include creating APIs and services for LLM interaction, building data pipelines and workflows, and ensuring secure and efficient deployment of LLM-based features. The role involves troubleshooting integration issues, optimizing system performance, and collaborating with product, data, and engineering teams to define requirements and deliver robust solutions. The engineer will also document integration processes, maintain technical standards, and contribute to continuous improvement of LLM tooling and infrastructure.
Qualifications
Candidates should possess strong Analytical Skills and Troubleshooting abilities to diagnose issues, interpret data, and improve system reliability.
Candidates should possess Software Development skills, including proficiency in one or more programming languages (such as Python, Java, or JavaScript) and experience building production-grade applications.
Candidates should possess Integration skills, including experience with APIs, microservices, and connecting third-party or AI services to existing platforms.
Candidates should possess Systems Engineering skills to design, deploy, and maintain scalable, secure, and resilient architectures for LLM-based solutions.
Experience working with LLMs or other machine learning models, including prompt engineering, model evaluation, and performance tuning, is highly beneficial.
Familiarity with cloud platforms (e.g., AWS, GCP, Azure), containerization (Docker, Kubernetes), and CI/CD pipelines is an advantage.
A bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience, is preferred.
Strong collaboration, communication, and documentation skills, with the ability to work closely with cross-functional teams and stakeholders.

Work arrangement
No