We are looking for an experienced Senior Generative AI Engineer to join our GenAI Solutions team. The ideal candidate will bring extensive expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI systems, along with a strong background in cloud-native development and enterprise-scale deployments.

This role is critical in driving our AI innovation strategy and delivering impactful, production-ready solutions for business transformation.

- Lead the end-to-end design, development, and deployment of Generative AI applications, including LLM-powered workflows, RAG pipelines, and Agentic AI solutions.

- Architect secure and scalable AI infrastructures using cloud platforms (GCP, AWS, Azure).

- Apply fine-tuning, advanced prompt engineering, and LLMOps best practices to enhance solution performance and relevance.

- Build, optimize, and maintain APIs and microservices (FastAPI, REST, Spring Boot) to integrate AI solutions into enterprise applications.

- Develop and manage data pipelines, vector databases, and Elasticsearch integrations for real-time knowledge retrieval and decision-making.

- Implement MLOps, CI/CD, and DevOps practices using Kubernetes, Docker, Jenkins, and Ansible for robust deployment and monitoring.

- Ensure high availability, logging, and performance monitoring through ELK stack and infrastructure-as-code practices.

- Collaborate with cross-functional teams to align AI solutions with business goals and operational requirements.

- Mentor and guide junior engineers, setting best practices for scalable AI development.

Experience :

- 2+ years of professional software engineering experience, with Generative AI/LLM application development.

Qualifications :

- A masters degree in computer science/applications/engineering.

- Proven expertise in LLMs, LangChain, LangGraph, RAG systems, and Agentic AI frameworks.

- Proficiency in Python (advanced).

- Strong knowledge of cloud platforms : GCP, AWS, Azure.

- Hands-on experience with MLOps & DevOps practices : Kubernetes, Docker, Jenkins, Ansible, Infrastructure-as-Code.

- Experience with databases and data pipelines : PostgreSQL, SQL, Vector Databases, Elasticsearch.

- Familiarity with API development frameworks : FastAPI.

- Excellent analytical and problem-solving skills with the ability to lead AI initiatives end-to-end.

- Strong communication skills with experience in working across cross-functional and distributed teams.