Senior Data Scientist with Generative AI (8+ Years)

Hiring: Senior Data Scientist – Generative AIExperience: 8+ Years of Relevant Experience

Work Mode: 100% Remote

Employment Type: C2C (Corp-to-Corp)

About the RoleWe are looking for an experienced Senior Data Scientist – Generative AI to join our AI Data Science team and contribute to the development and continuous improvement of advanced AI capabilities across Contact Center and Unified Communications products.

In this hands-on technical role, you will work on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, evaluation frameworks, experimentation, and optimization. You will focus on improving how AI agents understand customer intent, retrieve relevant knowledge, select and execute tools, manage context, and complete complex multi-step tasks.

The ideal candidate will have strong Python programming skills, practical experience with Generative AI applications, and a proven ability to take AI solutions from experimentation to production using provider-hosted LLMs.

Key Responsibilities

• Design, develop, evaluate, and optimize Generative AI solutions for AI-powered products and platforms.
• Improve AI agent performance across reasoning, tool selection, tool execution, knowledge retrieval, context management, personalization, and multi-step task completion.
• Develop and optimize prompts, structured instructions, context-building strategies, and structured output generation.
• Build and enhance RAG pipelines, including embeddings, semantic search, retrieval strategies, ranking, and context selection.
• Experiment with different LLMs, prompts, retrieval configurations, agent instructions, and tools to identify optimal solutions.
• Design evaluation frameworks, benchmarks, metrics, test scenarios, and datasets to measure accuracy, relevance, reliability, safety, and task completion.
• Conduct offline and online experiments to compare AI approaches and measure their impact on customer experience and business outcomes.
• Identify and mitigate AI failure modes, including hallucinations, irrelevant retrieval, inconsistent responses, and unsuccessful tool execution.
• Analyze production traces, agent behavior, evaluation results, and customer feedback to identify performance gaps and improvement opportunities.
• Collaborate with software engineers, AI/ML engineers, product managers, and domain experts to integrate AI capabilities into production systems.
• Implement responsible AI safeguards, including grounding, output validation, privacy protection, security controls, and prompt-injection prevention.
• Develop maintainable, well-tested, production-quality Python code and contribute to scalable, reliable, and observable AI services.Required Qualifications
• 8+ years of relevant professional experience in Data Science, Applied AI, Machine Learning, Software Engineering, or a related field.
• Demonstrated hands-on experience developing and improving Generative AI applications using Large Language Models.
• Strong proficiency in Python programming, including writing maintainable, tested, production-ready code.
• Practical experience with LLM integration, prompt engineering, structured outputs, and context management.
• Strong understanding of Retrieval-Augmented Generation (RAG), embeddings, vector search, semantic retrieval, and ranking techniques.
• Experience designing AI evaluation methodologies, benchmarks, test datasets, and performance metrics.
• Experience conducting experiments to compare model configurations, prompts, retrieval approaches, and agent behaviors.
• Ability to troubleshoot LLM-related issues, analyze failure patterns, and implement effective improvements.
• Understanding of AI safety, responsible AI practices, data privacy, and security considerations.
• Strong analytical, problem-solving, communication, and cross-functional collaboration skills.
• Ability to independently manage complex technical assignments and make sound decisions when requirements are ambiguous.Preferred Qualifications
• Experience with conversational AI, voice AI, or contact center automation.
• Familiarity with LLM observability, tracing, monitoring, and evaluation platforms.
• Experience with vector databases and knowledge retrieval systems.
• Exposure to AI agent frameworks, tool-calling architectures, and multi-step workflows.
• Experience deploying or integrating LLM-powered capabilities into scalable production environments.
• Familiarity with Contact Center as a Service (CCaaS) or Unified Communications as a Service (UCaaS) platforms.Role ExpectationsThis is an individual-contributor position focused on hands-on technical execution, experimentation, and continuous product improvement. The successful candidate will work within established product and platform priorities, collaborate closely with cross-functional teams, and contribute to delivering reliable, high-quality Generative AI capabilities.

Interested candidates: Please share your updated resume highlighting relevant experience in Generative AI, LLMs, RAG, AI agents, evaluation frameworks, and Python.