Sr. Engineer Data Scientist – Gen AI

Sr. Engineer Data Scientist – Gen AI page is loaded## Sr. Engineer Data Scientist – Gen AIremote type : Hybridlocations : Colombia - Remotetime type : Full timeposted on : Posted Todayjob requisition id : JR For more than 40 years, Accelya has been the industry’s partner for change, simplifying airline financial and commercial processes and empowering the air transport community to take better control of the future. Whether partnering with IATA on industry-wide initiatives or enabling digital transformation to simplify airline processes, Accelya drives the airline industry forward and proudly puts control back in the hands of airlines so they can move further, faster. We are looking for a Senior Data Scientist to work on projects that apply Large Language Models (LLMs) and AI agents in production environments. You will be at the forefront of designing domain-adapted generative solutions, enabling capabilities such as structured output generation and schema-constrained applications that drive operational impact.While the main focus will be GenAI initiatives, you will also contribute to traditional ML projects (e.g., predictive modeling, demand forecasting, optimization, and time series analysis) as needed, based on company priorities.If you are passionate about LLMs, prompt engineering, fine-tuning, and building robust agentic systems, and if you thrive at the intersection of AI research and production deployment, this role is for you.Responsibilities

• Design and implement LLM-powered solutions for enterprise-scale use cases requiring structured outputs and domain adaptation.
• Develop and maintain AI agents capable of handling domain-specific knowledge and workflows in production.
• Apply prompt engineering, retrieval-augmented generation (RAG), and other techniques to embed company expertise into LLM pipelines.
• Contribute to LLM continuous pretraining and fine-tuning efforts to adapt models to specialized tasks.
• Integrate LLM-based agents into production environments with a focus on scalability, latency, reliability, and compliance.
• Conduct experiments to evaluate model quality, effectiveness, and business impact.
• Establish monitoring, guardrails, and evaluation frameworks for safe and effective GenAI usage.
• Stay current with research and developments in LLMs, agent architectures, orchestration frameworks, and generative AI platforms.
• Use predictive modeling to enhance customer experience, revenue generation, dynamic pricing, and demand forecasting.
• Communicate complex findings and insights to both technical and non-technical audiences.
• Collaborate with different functional teams to integrate models into business operations.Required Qualifications
• Strong understanding of LLMs, GenAI, and AI agent architectures.
• Solid understanding of fine-tuning and continuous pretraining approaches (experience is a strong plus).
• Proven expertise in prompt engineering and methods for grounding LLMs with domain-specific data.
• Demonstrated experience in deploying AI agents into production, including integration with APIs, databases, and business systems.
• Expertise in machine learning algorithms such as regression, classification, clustering (GLM, Random Forest, Gradient Boosting, deep learning, etc.).
• Solid understanding of statistical techniques (regression, distributions, hypothesis testing).
• Proficiency in Python and familiarity with ML / AI frameworks (e.g., PyTorch, TensorFlow).
• Strong problem-solving skills and ability to translate business requirements into GenAI or traditional ML solutions.
• Excellent communication skills for cross-functional collaboration and for explaining technical concepts to non-technical audiences.Fluent English : Interviews will be held in this laguage.Preferred Qualifications
• Hands-on experience with LangChain, AWS Bedrock, or equivalent LLM orchestration and hosting platforms.
• Hands-on experience in fine-tuning or continuous pretraining of LLMs.
• Experience with retrieval-augmented generation (RAG), semantic search, and hybrid search approaches.
• Background in structured output generation, such as schema-constrained documents or domain-specific query generation.
• Knowledge of airline, travel, or pricing / revenue management domains.
• Experience with Databricks, PySpark, or other large-scale data processing tools.
• Familiarity with evaluation of generative AI systems, including human-in-the-loop validation, A / B testing, and automated metrics.
• Degree in Computer Science, AI / ML, Applied Mathematics, or related field.At Accelya, you will work at the intersection of data science and aviation, tackling real-world challenges that impact global airlines. You will have the opportunity to work with large, complex datasets, apply state-of-the-art machine learning techniques, and collaborate with a highly skilled team of data scientists, engineers, and business leaders.Your work will directly influence how airlines optimize their pricing, forecast demand, and maximize revenue. If you have a background in revenue management, dynamic pricing, or cloud-based AI / ML, you will have an opportunity to apply your skills on a global scale.

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