AI Engineer

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.

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

• A master's 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.

• Domain experience in automotive, manufacturing, or enterprise AI solutions.
• Background in enterprise-grade AI security and compliance.
• Exposure to frontend integration frameworks (ReactJS) for AI-enabled applications.