About the Role
We are looking for an experienced Senior AI/ML Engineer with a strong background in Generative AI and Large Language Models (LLMs) to join our team. In this role, you will design and implement advanced AI-driven solutions that enhance system engineering processes and customer interactions. You will work on cutting-edge projects that integrate Agentic AI, RAG pipelines, and scalable deployment strategies, collaborating with multidisciplinary teams and industry leaders to deliver impactful solutions.
What You’ll Do
- Design and implement automated workflows and AI-driven solutions for complex business and engineering challenges.
- Develop and prototype Generative AI applications, including digital engineering assistants and knowledge management tools.
- Integrate LLMs into production environments, ensuring scalability, security, and performance.
- Collaborate with research and engineering teams to identify opportunities for AI integration and provide methodological recommendations.
- Mentor team members, share best practices, and present learnings to stakeholders.
- Stay up to date with emerging AI trends and assess their potential impact on future projects.
Required Skills & Experience
- Strong Python skills and hands-on experience with LLMs and Generative AI (OpenAI, Anthropic, Google Gemini, Hugging Face, etc.).
- Expertise in prompt engineering, fine-tuning, and adapter-based methods.
- Practical knowledge of RAG (Retrieval-Augmented Generation), embeddings, and vector databases (Pinecone, ChromaDB, Weaviate, Qdrant, pgvector).
- Familiarity with agent frameworks (LangChain, LlamaIndex, Google ADK / Vertex AI Agent Builder).
- Experience deploying AI models and services to production using Docker, CI/CD, and cloud platforms (GCP preferred; Azure or Databricks experience is a plus).
- Strong understanding of system design, distributed systems, and AI evaluation frameworks.
- Ability to communicate complex AI concepts to diverse stakeholders and work in multidisciplinary teams.
Preferred Qualifications
- Degree in Computer Science, Engineering, Data Science, or related field.
- Knowledge of graph-based knowledge integration (GraphRAG) and scalable AI deployment strategies.
- Experience with FastAPI, REST/gRPC, and exposing AI services via APIs.
