Our client, a leading and well-established financial services organization, is developing a next-generation AI-driven content platform designed to deliver intelligent trading insights and personalized financial experiences. They are seeking a Lead AI Engineer to drive the design, development, and deployment of cutting-edge AI solutions within a highly regulated environment.
This is a senior leadership role suited for a hands-on AI expert with deep experience in large language models (LLMs), open-source AI technologies, recommendation systems, and scalable machine learning platforms. The successful candidate will play a pivotal role in shaping AI strategy, architecture, and innovation while leading the delivery of production-grade AI applications.
Key Responsibilities
AI Solution Design & Development
- Lead the development and optimization of advanced AI solutions, including large language models (LLMs), multimodal AI systems, and generative AI applications focused on trading and financial content.
- Design and implement intelligent personalization engines that deliver relevant content, insights, and recommendations based on user behavior and preferences.
- Develop scalable search and recommendation systems utilizing techniques such as graph analytics, embeddings, vector search, and behavioral modeling.
AI Platform Architecture & Engineering
- Architect, build, and manage end-to-end AI/ML platforms spanning data ingestion, feature engineering, model training, fine-tuning, deployment, monitoring, and lifecycle management.
- Establish robust model evaluation and experimentation frameworks to continuously improve accuracy, relevance, and user engagement.
- Design real-time data pipelines that process high-volume market, transactional, and user interaction data to support low-latency AI applications.
Model Fine-Tuning & Governance
- Own and enhance custom model fine-tuning workflows using open-source AI frameworks and tooling.
- Ensure AI systems comply with regulatory, security, risk, and data governance requirements, including KYC, AML, privacy, and auditability standards.
- Drive best practices around model performance, reliability, explainability, and responsible AI implementation.
Leadership & Stakeholder Management
- Provide technical leadership, coaching, and mentorship to AI, data engineering, and machine learning teams.
- Partner closely with Product, Engineering, Data, Compliance, and Business stakeholders to transform business challenges into scalable AI solutions.
- Influence strategic decisions related to AI architecture, platform scalability, operational excellence, and cost optimization.
Required Experience & Qualifications
- Bachelor's degree or higher in Computer Science, Artificial Intelligence, Engineering, Data Science, or a related discipline.
- 10+ years of experience across AI, Machine Learning, Data Science, or Data Engineering, with extensive exposure to enterprise-scale production environments.
- Proven experience designing, deploying, and managing AI-powered applications and LLM-based solutions in production.
- Strong hands-on expertise with open-source AI frameworks, including:
- PyTorch
- Hugging Face Ecosystem
- Transformers
- LangChain/LlamaIndex (preferred)
- Deep knowledge of model fine-tuning, evaluation methodologies, prompt engineering, and optimization techniques.
- Strong experience building feature stores, large-scale data pipelines, and real-time machine learning systems.
- Solid understanding of recommendation systems, ranking algorithms, graph-based learning, vector databases, and user personalization techniques.
- Experience working within regulated industries such as financial services, banking, fintech, or capital markets would be highly advantageous.
- Strong communication skills with the ability to influence stakeholders and lead cross-functional initiatives.
Please share your updated resume to *************