I
Senior AI Engineer
Iris Software Inc.
2 hours ago
Full-time
On-site
Raleigh, North Carolina, United States
Iris Software's client one of the leading Bank is looking to hire for the following roles
Hybrid: 3- 4 days onsite
Key Responsibilities: Design and build Agentic AI and Generative AI frameworks to solve critical sales use cases such as client intelligence, pitch generation, deal summarization, and real-time conversation analysis.
Develop conversational AI solutions that assist sales professionals with client interactions and synthesize intelligence from multiple enterprise data sources.
Embed Generative AI capabilities into Sales platforms to support prospect research, proposal generation, deal tracking, and intelligent sales workflows.
Build and architect end-to-end AI solutions, including experimentation, model evaluation, deployment, observability, and production monitoring at scale.
Develop solutions using Python, LLMs, RAG, agentic frameworks, embeddings, re-rankers, vector databases, context management, memory, and tool/skills integration patterns.
Work extensively with Anthropic/Claude models, including Claude-based code generation, LLM inference, fine-tuning, and model deployment.
Apply strong knowledge of machine learning/deep learning, algorithms, data structures, distributed computing, and production ML experimentation and evaluation.
Follow enterprise engineering practices including CI/CD, code reviews, unit testing, quality gates, open-source/security scans, Aqua scans, and remediation of identified issues.
Provide technical guidance, conduct code reviews, mentor team members, and promote AI-first development practices while adapting solutions to evolving Generative AI technologies and enterprise standards.
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Hybrid: 3- 4 days onsite
Key Responsibilities: Design and build Agentic AI and Generative AI frameworks to solve critical sales use cases such as client intelligence, pitch generation, deal summarization, and real-time conversation analysis.
Develop conversational AI solutions that assist sales professionals with client interactions and synthesize intelligence from multiple enterprise data sources.
Embed Generative AI capabilities into Sales platforms to support prospect research, proposal generation, deal tracking, and intelligent sales workflows.
Build and architect end-to-end AI solutions, including experimentation, model evaluation, deployment, observability, and production monitoring at scale.
Develop solutions using Python, LLMs, RAG, agentic frameworks, embeddings, re-rankers, vector databases, context management, memory, and tool/skills integration patterns.
Work extensively with Anthropic/Claude models, including Claude-based code generation, LLM inference, fine-tuning, and model deployment.
Apply strong knowledge of machine learning/deep learning, algorithms, data structures, distributed computing, and production ML experimentation and evaluation.
Follow enterprise engineering practices including CI/CD, code reviews, unit testing, quality gates, open-source/security scans, Aqua scans, and remediation of identified issues.
Provide technical guidance, conduct code reviews, mentor team members, and promote AI-first development practices while adapting solutions to evolving Generative AI technologies and enterprise standards.
#J-18808-Ljbffr