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 (ref : hirist.tech)