Client

Our client is a leading travel company undertaking a major technology transformation to decouple the frontend user experience from its legacy backend booking engine, enabling greater agility, ownership of mission-critical technologies, and enhanced responsiveness in a fast-evolving travel industry.

Join a great company, not merely an individual project

Position overview

We are seeking a skilled and innovative Generative AI / Machine Learning Engineer to serve as a key technical leader in developing the Itinerary Intelligence Microservice (IIMS). This platform aims to enhance travel content automation for our client.

In this role, you will design, develop, and deploy a suite of AI-powered microservices that parse, enrich, compare, and visualize complex travel itineraries. This hands-on position requires strong expertise in Python, cloud services (preferably AWS), large language model (LLM) application development, and DevOps practices. You will contribute to a high-priority MVP project focused on transforming unstructured data from diverse sources into structured, valuable assets.

Responsibilities

• Design, build, and maintain the core Python microservices for the IIMS platform.
• Implement and refine the pipeline that uses vision-capable LLMs (e.g., GPT-4 series) to extract structured data from PDF, DOCX, and TXT files.
• Engineer prompts and logic to enhance extracted content, generating compelling, market-ready descriptions for travel components.
• Build the functionality to programmatically compare two document versions and generate a structured summary of differences.
• Create the logic to match extracted components (hotels, tours) against a PostgreSQL catalog using fuzzy search techniques and LLM-driven decision-making.
• Lead research spikes to test, validate, and iteratively improve the performance of prompts and select the optimal LLM for each specific task (balancing cost, speed, and accuracy).
• Design and expose clean, robust, and well-documented FastAPI endpoints for each microservice.
• Containerize the application using Docker for consistent deployment and scalability within an AWS cloud environment. Contribute to CI/CD pipeline setup and maintenance.
• Collaborate on the design of the end-to-end processing pipeline, ensuring services are resilient, scalable, and efficient.
• Quickly build and test technical proofs-of-concept for new features, such as the AI-powered video generation service, evaluating external APIs and integration strategies.

Requirements

• Proven, hands-on experience developing complex applications and services in Python. Proficiency with modern Python (3.10+) and its asynchronous capabilities (asyncio).
• Demonstrable experience building applications that integrate with Large Language Models.
• Deep understanding of prompt engineering principles.
• Experience with the most common LLMs APIs (including Chat Completions and Assistants/File APIs).
• Experience working with Amazon Bedrock or Amazon Nova.
• Familiarity with handling and processing unstructured data.
• Strong experience deploying and managing applications in a cloud environment, preferably AWS. Familiarity with core services such as EC2, S3, Lambda, and IAM.
• Solid understanding of DevOps principles and hands-on experience with Docker for creating, managing, and deploying containerized applications.
• Proficient in designing, building, and consuming RESTful APIs. Experience with web frameworks like FastAPI or Flask is essential.

Nice to have

• Experience with multimodal models (processing both text and images/files).
• Knowledge of PostgreSQL, including experience with extensions like pg_trgm for fuzzy text searching.
• Familiarity with Natural Language Processing (NLP) techniques and libraries.
• Experience with Infrastructure as Code (IaC) tools like Terraform.