Sr. Gen AI Engg - Recommendation Systems.

Our client which is a large Investment Bank is urgently looking to hire a Sr. Gen AI Engg - Recommendation Systems.

Sr. Gen AI Engg - Recommendation Systems.

Location - Raleigh, NC

Hybrid - Need 4 days onsite every week.

F2F is required.

Skills - GEN AI - Anthropic / Claude, Neural Networks, RAG, Deep Learning, Machine Learning, Recommendation Systems ( Re-Ranker, Vector Databases, Embeddings, neural networks, Memory Management), Python, LLMs

AI Engineer

Our Client is seeking an AI Engineer with deep expertise in Generative AI, neural networks, and transfer learning to support Sales teams with cutting-edge AI-powered solutions. You will lead the design and development of intelligent systems that enhance client engagement, deal intelligence, and sales productivity across Capital Markets.

The Capital Markets Data AI and Research Technology (DART) team is looking for a hands-on AI Engineer to drive Generative AI initiatives that empower our Sales organization. You will build and deploy AI solutions that give sales professionals real-time insights, automate routine tasks, and enable them to focus on client relationships and closing deals.

What will you do?

Design and build agentic frameworks that solve critical sales use cases including client intelligence gathering, pitch content generation, deal summarization, and real-time conversation analysis. Develop conversational AI systems that assist sales professionals in client interactions and help synthesize client intelligence across multiple data sources. Embed Generative AI tools into Sales platforms, enabling seamless workflows for prospect research, proposal generation, and deal tracking. Architect end-to-end AI solutions covering experimentation, model evaluation, and production monitoring to ensure sales tools perform reliably at scale. Guide the team on best practices, conduct code reviews, and mentor team members on Generative AI implementation.

What do you need to succeed?

• Must-have Degree in Computer Science, Machine Learning, Deep Learning, or equivalent hands-on experience.
• 2-5 years building Deep Learning or Machine Learning models in production environments.
• Advanced proficiency in Python and hands-on experience with Generative AI frameworks and architecture.
• Deep knowledge of retrieval-augmented generation (RAG), agentic frameworks, context and memory management, and tool/skills integration patterns.
• Strong understanding of large language model architectures, inference, fine-tuning, and model deployment.
• Experience with Anthropic models and Claude, including code generation capabilities. In-depth knowledge of embeddings, re-rankers, and vector databases.
• Expertise in ML experimentation, model evaluation, and monitoring in production.
• Strong foundation in algorithms, data structures, and distributed computing.
• Understanding of Enterprise standards or having prior experience of working with enterprise team, ability to learn on the job and adaptive the change.

Embraces an AI-first approach:

• Someone who actively incorporates AI tools and technologies into daily workflows to enhance productivity, streamline routine tasks, and drive efficiency. Demonstrates curiosity about emerging AI capabilities and applies them thoughtfully to deliver better outcomes for clients and internal stakeholders.
• Strong understanding of CI and CD.
• Also good understanding of code review and quality gate checks such as unit code tests, open source scans , aqua scans etc. and worked on fixing these.