Role Description This is a back-end, non-customer-facing role. You'll work directly with our software team to make sure every listing is set up correctly inside our property management system, channel manager, pricing engine, and supporting tools. You'll be the bridge between our software systems and our front-end listing specialists, freeing them up to focus on partners and properties. If you're detail-oriented, systems-minded, and you like the satisfaction of turning messy data into clean systems that run smoothly, this role is for you. What You'll Do - System Setup and Configuration - Configure new properties inside HostAway, Breezeway, PriceLabs, Charge Automation, Authenticate, and our proprietary tools. - Build out channel connections to Airbnb, VRBO, Expedia, Booking.com, and other distribution platforms. - Set up automations, message templates, fees, taxes, and policies inside our PMS. - Listing Data and Quality - Audit existing listings for missing or inaccurate data and fix the gaps. - Maintain our central amenities database and keep property attributes consistent across every platform. - Verify rates, availability, minimum stays, and policies are accurate everywhere a listing appears. - Software Team Support - Work directly with our developers on testing, bug reporting, and rolling out new internal tools. - Help migrate data between systems during partner onboarding. - Document processes and build SOPs as our systems evolve. - Front-End Team Support - Be the back-end resource our listing specialists rely on to get things done in the software. - Troubleshoot integration issues, sync errors, and platform problems so the front-end team can keep moving. - Flag patterns that suggest a system improvement is needed. Qualifications - Fluent written and spoken English is required. All work, training, documentation, and team communication happen in English. - Comfortable in software systems and tools, with sharp attention to detail. - Self-directed and reliable in a fully remote environment. - Experience with PMS or channel manager platforms (HostAway, Guesty, Hospitable, OwnerRez, etc.) is a strong plus. - Experience in the short-term rental industry is a plus but not required. Compensation and Schedule - Salary: $500 USD per month - Start date: Early July 2026 - Status: Full-time, 40 hours/week - Schedule: Monday to Friday, 8:00 AM to 5:00 PM CST, with Mandatory Virtual Office Hours from 8:00 AM to 12:00 PM CST. - Overtime: We try to avoid it and it shouldn't be necessary, but if it's absolutely necessary we will pay at 1.5x your daily salary rate. - Payments: Made monthly on the last business day of each month. We'll request your bank details directly from our bank (most of our team uses Wise). - Productivity and Time Tracking: Trackabi is required for all working time.

Role Description As a consultant Systems Support Engineer you will play a vital role in supporting the day-to-day operations of application systems. This role involves actively contributing to incident management and gaining exposure to DevOps practices. Your efforts will contribute to the smooth functioning of systems and you'll have the opportunity to learn and grow while assisting in the delivery of solutions to our clients. - You will work with incident management process and tools. - You will use complex application systems and find your way through them to debug a business impacting issue. - You will follow standards and best practices to bring operational efficiencies, stability and availability of the system. - You will use continuous delivery practices to evolve, support and deliver high-quality software, as well as value to end customers, as early as possible while working in collaborative, value-driven teams to build innovative customer experiences for our clients. - You will leverage your knowledge regarding different logging techniques (various levels) and use them for alerting, monitoring and identifying the root cause of incidents. - You will derive meaningful reports/key performance indicators and set up alerting and monitoring mechanisms for quicker identification of incidents and response. - You will apply the latest technology thinking from our Technology Radar to solve client problems. Qualifications - You have experience working with programming languages such as Node, React, TypeScript. - You have an understanding of cloud platforms such as AWS, Azure or GCP. - You are familiar with scripting languages such as Python and PowerShell. - You understand how to use debugging tools and how to troubleshoot issues with the code. - You have experience working with relational or non-relational databases. - You have experience working with CI/CD tools such as Jenkins or Azure pipelines. - You have exposure to application monitoring tools such as DataDog, Prometheus or Grafana. - You are comfortable with Agile methods such as Scrum and/or Kanban. - You have the ability to ensure that the deliverables, namely bug fixes and enhancements to the existing codebase, are of high quality and well-tested. Requirements - You have strong communication and articulation skills, are proficient in English and able to confidently hold a Q&A discussion with senior stakeholders. - You have good communication and articulation skills. - You have a presence in the external tech community and willingly share your expertise with others via speaking engagements, contributions to open source, blogs and more. - You are resilient in ambiguous situations and can approach challenges from multiple perspectives. - You are willing to be part of a rotation- and need-based 24x7 team and are able to handle multiple engagements. Benefits - There is no one-size-fits-all career path at Thoughtworks; however, you want to develop your career is entirely up to you. - Your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. - We see value in helping each other be our best and that extends to empowering our employees in their career journeys. Company Description Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work. For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator. Bring your brilliant expertise and commitment for continuous learning to Thoughtworks. Together, let’s be extraordinary.

• Architect, build, and operate scalable backend services for a media intelligence platform, with a focus on clean, maintainable, and production-ready systems. • Own critical backend components end to end, from system design and API contracts through implementation, deployment, monitoring, and iteration. • Drive architectural decisions across APIs, processing pipelines, distributed compute, storage, search, observability, cloud infrastructure, and model-serving workflows. • Design data models and storage patterns for media assets, generated metadata, embeddings, processing jobs, model outputs, search indexes, and audit trails. • Design high-throughput media ingestion and processing pipelines for large volumes of video, audio, image, and text content. • Build distributed, event-driven workflows for media processing using queues and pub/sub systems such as SQS, Kafka, Pub/Sub, or equivalent technologies. • Implement reliable asynchronous processing patterns, including retries, idempotency, dead-letter queues, backpressure handling, and fault-tolerant job execution. • Lead the development and optimization of metadata extraction, content analysis, scene detection, transcription, embedding generation, and multimodal AI inference workflows. • Integrate and optimize AI/ML services within backend workflows, including model APIs, embedding pipelines, OCR, speech-to-text, scene analysis, multimodal inference, batching, caching, and fallback strategies. • Collaborate with ML engineers, data scientists, or external model providers to benchmark models, compare quality/latency trade-offs, and safely roll out model upgrades. • Optimize AI/ML inference workflows for latency, throughput, reliability, and cost across both real-time and batch-processing paths. • Work with model-serving systems such as vLLM, Triton, TGI, SageMaker, Vertex AI, or custom inference services to improve batching, concurrency, warmup behavior, timeout handling, autoscaling, and GPU utilization. • Evaluate and apply practical model optimization techniques such as quantization, model distillation, batching, caching, prompt optimization, and routing to smaller or cheaper models where appropriate. • Design and maintain vector search and indexing systems using technologies such as Pinecone, Weaviate, Qdrant, Elastic Vectors, FAISS, pgvector, or similar tools. • Build retrieval workflows that support semantic search, similarity matching, duplicate detection, media discovery, and structured metadata search. • Deploy and operate systems on AWS, GCP, Azure, or equivalent cloud platforms, including compute, storage, networking, queues, model-serving infrastructure, and monitoring systems. • Ensure system reliability through logging, metrics, tracing, alerting, dashboards, operational runbooks, and incident-response best practices. • Collaborate with product, design, data, and ML teams to deliver media-rich, AI-powered product features. • Mentor junior and mid-level engineers, support technical planning, review designs, and raise engineering quality across the team. • Participate in code reviews, documentation, technical planning, and continuous improvement of engineering practices. • Ensure code quality through testing, peer review, clear documentation, and maintainable implementation patterns.

• Architect, build, and operate scalable backend services for a media intelligence platform, with a focus on clean, maintainable, and production-ready systems. • Own critical backend components end to end, from system design and API contracts through implementation, deployment, monitoring, and iteration. • Drive architectural decisions across APIs, processing pipelines, distributed compute, storage, search, observability, cloud infrastructure, and model-serving workflows. • Design data models and storage patterns for media assets, generated metadata, embeddings, processing jobs, model outputs, search indexes, and audit trails. • Design high-throughput media ingestion and processing pipelines for large volumes of video, audio, image, and text content. • Build distributed, event-driven workflows for media processing using queues and pub/sub systems such as SQS, Kafka, Pub/Sub, or equivalent technologies. • Implement reliable asynchronous processing patterns, including retries, idempotency, dead-letter queues, backpressure handling, and fault-tolerant job execution. • Lead the development and optimization of metadata extraction, content analysis, scene detection, transcription, embedding generation, and multimodal AI inference workflows. • Integrate and optimize AI/ML services within backend workflows, including model APIs, embedding pipelines, OCR, speech-to-text, scene analysis, multimodal inference, batching, caching, and fallback strategies. • Optimize AI/ML inference workflows for latency, throughput, reliability, and cost across both real-time and batch-processing paths. • Evaluate and apply practical model optimization techniques such as quantization, model distillation, batching, caching, prompt optimization, and routing to smaller or cheaper models where appropriate. • Monitor model and system performance in production, including API latency, queue depth, processing time, model error rates, GPU utilization, confidence distributions, drift signals, and cost per processed item.