RandomTrees - Artificial Intelligence Architect/Senior Artificial Intelligence Engineer

Description :

Random Trees seeking an experienced AI Architect/Senior AI Engineer to lead the design, development, and deployment of advanced AI/ML solutions.

The ideal candidate will have strong expertise in Machine Learning, Deep Learning, NLP, Generative AI, Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), Lang Chain, and MLOps.

Proficiency in Python and SQL is essential.

This role requires a mix of hands-on technical expertise, solution architecture, and leadership to deliver scalable and business-driven AI solutions.

Key Responsibilities :

- Design and architect end-to-end AI/ML solutions aligned with business goals.

- Develop and integrate Machine Learning, Deep Learning, and NLP models into production environments.

- Architect and implement LLM-based solutions including RAG pipelines, prompt engineering, fine-tuning, and LangChain frameworks.

- Collaborate with data engineers to build data pipelines, ensure data quality, and optimize SQL-based data processing.

- Drive adoption of Generative AI applications across use cases such as chatbots, summarization, recommendation engines, and content generation

- Experience with Agentic AI frameworks for building autonomous and goal-driven AI agents.

- Establish and implement MLOps best practices for model lifecycle management, CI/CD, monitoring, retraining, and scalability.

- Evaluate emerging AI/ML frameworks and tools and provide recommendations for adoption.

- Partner with stakeholders to translate business requirements into AI/ML architectural blueprints.

- Ensure compliance with AI governance, security, and ethical AI practices.

- Mentor and guide engineering teams on AI/ML solution design, coding standards, and deployment strategies.

Required Skills & Qualifications :

- Bachelors or masters degree in computer science, Data Science, AI/ML, or related field.

- 7+ years of experience in AI/ML with proven solution architecture expertise.

- Strong hands-on experience in Machine Learning, Deep Learning (TensorFlow, PyTorch, Keras), and NLP (Hugging Face, spaCy, NLTK).

- Expertise in Generative AI, LLMs (GPT, LLaMA, Claude, etc.), RAG, and LangChain.

- Proficiency in Python (NumPy, Pandas, Scikit-learn, FastAPI/Flask) and SQL.

- Experience with Agentic AI frameworks for building autonomous and goal-driven AI agents.

- Strong experience in MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes, CI/CD pipelines).

- Knowledge of cloud platforms (AWS, Azure, GCP) and their AI/ML services.

- Experience in vector databases (Pinecone, Weaviate, FAISS, Milvus) for RAG and LLM applications.

- Familiarity with data governance, model explainability, bias detection, and responsible AI practices.

- Excellent problem-solving, communication, and stakeholder management skills.

Good to Have :

- Experience in multi-modal AI (text, image, video, audio).

- Exposure to Graph Neural Networks (GNNs), reinforcement learning, or time-series forecasting.

- Prior experience in leading AI CoEs (Centers of Excellence) or enterprise-scale AI transformations.

- Contributions to open-source AI/ML projects.

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