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.

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