• Build and deploy scalable AI products leveraging LLMs to support Yuno’s payment orchestration platform. • Develop and optimize prompts to ensure high-quality outputs from LLMs for specific use cases, such as customer service, fraud prevention, and payment assistance. • Design, test, and iterate prompts to achieve optimal performance for AI models. • Analyze and refine outputs based on feedback loops and user interaction data. • Collaborate with cross-functional teams to integrate AI features into existing payment systems and workflows. • Ensure seamless interaction between AI solutions and Yuno’s core services. • Stay updated on advancements in LLMs, prompt engineering, and related AI fields. • Experiment with emerging technologies to identify opportunities for Yuno’s product innovation. • Leverage payment and user interaction data to fine-tune AI models and improve product performance. • Ensure adherence to data privacy regulations and best practices in AI ethics.

• Join our world-class engineering team in building the Verisian Platform • Use the latest in AI, specifically LLMs and RAG systems, to create Coding Agents, Analysis/Results Validation Agents, Submission Documentation Agents, and Onboarding/QA/Exploration Agents • Work on core modules of the platform targeting planning, exploration/onboarding, building, validation, and submission of clinical trials • Analyze clinical trial documentation, code, logs, data, and results to build a knowledge graph through code traceability • Develop and deploy strategies for AI stack including production readiness, testing, and validations • Collaborate with the core team to design, build, and enhance platform functionalities • Autonomously handle issues identified in our Validator • Construct processes that ensure user impact and performance

Role Description Our client is a well-funded, venture-backed AI platform company on a mission to make life-saving drugs accessible and affordable for everyone. As their founding forward deployed engineer, you'll be the first hire on a new team sitting at the intersection of the product and enterprise customers. You’ll split time between core product engineering and building within their customers’ environments. Success in this role means: - Understanding the customers’ data environments. - Deploying and configuring the platform. - Building custom integrations and workflows. - Ensuring the product delivers real, measurable value. This is not a sales engineering or solutions consulting role. You will write production code in the customer's environment, on their data with an expectation that ~80% of what you build merges back into the main platform. You will also heavily influence the product roadmap by serving as a critical feedback loop between customers and the internal product and engineering teams. The product surface spans: - An operational data platform. - An AI-powered document intelligence layer distributed natively on Snowflake. - A raw material variability and genealogy analytics product. - A GxP-grade AI agent for shop-floor decision-making that integrates with MES, QMS, and LIMS systems. Please note that while the overwhelming majority of forward deployed work happens remotely, there is very occasional travel (roughly twice annually) to customer sites across North America and Europe. Qualifications - 6+ years of experience as a software engineer. - Recent experience with field deployments and shipping software inside customer environments. - Comfortable with Python, production-grade system design, and async patterns. - Experience shipping LLM-enabled features and products. - Familiar with prompt engineering, schema validation, and cost/latency optimization. - Experience deploying and operating AWS (or comparable) infrastructure with Terraform. - Fantastic command of English, comfortable presenting to executive stakeholders and pairing with hands-on engineers. - Practical handle on security and compliance constraints (SOC 2, HIPAA, GxP, or similar). - Comfortable working with fuzzy problems and have a high sense of ownership over your work. Requirements - Translate customer needs and pain points into actionable signals for the internal product and engineering teams. - Own the platform deployment into enterprise pharma and manufacturing accounts from kickoff through go-live. - Build connectors between customer systems and the platform. - Configure and extend AI-powered document processing pipelines for customer document types. - Navigate security reviews, SSO integrations, and compliance requirements alongside customer teams. - Represent the company technically in customer meetings, workshops, and executive briefings. - Create technical documentation, runbooks, and integration guides. Benefits - Base pay range of $180,000 – $230,000 per year (in local currency) + bonus + equity. Company Description Our client prioritizes talent density and has built a high-ownership, high-autonomy environment with a track record of fostering accelerated professional development.

• Own features end-to-end — from task breakdown to production deploy • Design and build server-side logic (REST and RPC APIs, services, integrations) • Implement user interfaces — clean and fast, without over-engineering • Set up CI/CD, containerisation, and feature-level infrastructure (DevOps basics) • Participate in code reviews, technical discussions, and task decomposition