- Company Name
- LSEG (London Stock Exchange Group)
- Job Title
- Principal AI Architect
- Job Description
-
**Job Title:** Principal AI Architect
**Role Summary:** Lead design, governance, and innovation of AI/ML platforms, ensuring technical excellence and cutting-edge capabilities through hands-on architecture leadership, mentorship, and cross-team collaboration. Drive research on emerging AI technologies to shape scalable, compliant solutions.
**Expectations:** Strategic leadership in AI/ML architecture, hands-on technical expertise in model and system development, innovation in generative AI and machine learning, and mentorship of AI/ML teams to foster technical best practices.
**Key Responsibilities:**
- Define and evolve AI/ML architecture for scalable, governed systems (Lakehouse, warehouse, etc.) with robust data lineage and performance.
- Conduct code/model reviews for quality, reproducibility, and adherence to best practices.
- Own and enhance AI/ML tooling (experiment tracking, pipelines, deployment, CI/CD, observability).
- Develop shared libraries/frameworks for model training, evaluation, and deployment.
- Research and integrate advancements in GenAI (LLMs, multimodal models) and ML frameworks (PyTorch, TensorFlow).
- Apply software engineering principles (SOLID, design patterns) to ensure maintainable, robust AI systems.
- Ensure responsible AI practices (fairness, explainability, compliance with governance standards).
- Collaborate with product/platform teams to deliver intelligent, scalable solutions.
- Mentor engineers/scientists to drive technical excellence and innovation.
**Required Skills:**
- Expertise in supervised, unsupervised, and generative AI/ML models.
- Deep understanding of model lifecycle (experimentation to production).
- Proven hands-on experience with LLMs, prompt engineering, LangChain, vector/graph databases, and RAG.
- Strong software engineering skills (SOLID, design patterns, scalable system design).
- Proficiency in ML tooling (MLflow, Databricks/Snowflake, MLOps) and cloud platforms (AWS, GCP, Azure).
- Experience deploying/monitoring AI/ML systems in production environments.
**Required Education & Certifications:**
- Bachelor’s/Master’s in Computer Science, AI/ML, or related field.
- Relevant certifications in AI/ML (e.g., TensorFlow, AWS ML Specialty) preferred.