Giant Leap Trainee

vaisalaoyj•Boston, MA

19d•$24 - $31•Hybrid

About The Position

Vaisala is a global leader in measurement instruments and intelligence helping industries, nations, people, and the planet to thrive. From predicting hurricanes to optimizing renewable energy production, our technology is used where it matters the most – from data centers, windfarms and laboratories to airports, the Arctic and even the surface of Mars. For a second year running, Vaisala got recognized in TIME Magazine's World's Best Companies in Sustainable Growth 2026 study. Our team of close to 2,500 experts and 62 nationalities around the world is committed to taking every measure for the planet. Driven by our shared purpose, curiosity, and pioneering spirit, we stay ahead and make a difference. At Vaisala, you don't have to fit in to belong. Are you ready to take a Giant Leap? We’re looking for a Giant Leap Trainee – AI Support Automation Developer in our Burlington, Massachusetts office. This is a full-time, hybrid, paid internship role from June to August. Giant Leap is a unique opportunity for you to be the project manager of your own project, with the support of your teammates and project supervisor. Every year, these projects are carefully selected by our leadership teams, meaning that you get to work on real-life questions that are important for us as a company. We invest in your growth with training sessions throughout the summer. Along with lessons from your own field and work life in general, you have a chance to learn, for instance, presentation skills, project management and problem solving. Connections built with fellow Giant Leapers, Vaisala’s brilliant experts and our leadership form an invaluable network for your career. Many of our former Giant Leapers have also gone on to build impressive careers at Vaisala after the program. We’re building and refining an AI-powered technical support assistant that helps our customers get faster, more accurate answers to complex support questions. Your mission is to help train and improve our AI tool (Taika) so that it can understand Vaisala’s products, interpret support cases, and provide high-quality, explainable responses. By doing this, you will help reduce manual case work, increase the speed and consistency of responses, and free our support experts to focus on the most challenging problems. A key focus of this role is training the AI to assist our Customer Care team in handling basic Tier 1 technical cases. You will help ensure that common, well-understood issues can be resolved quickly and accurately with AI-augmented assistance, while more complex cases are efficiently escalated appropriately. You will work with our Digital Excellence team, contributing to the integration of AI into our Salesforce CRM and, potentially, other internal tools and platforms.

Requirements

Familiarity with backend development and web APIs (e.g., Python, Node.js, or similar) and an interest in learning how AI systems integrate into production environments.
Understanding of modern AI / machine learning concepts, especially: Large Language Models (LLMs) and prompt engineering.
Retrieval-augmented generation (RAG) or similar patterns that combine search with AI responses.
Evaluation of AI outputs (accuracy, relevance, safety, and explainability).
Exposure (coursework or projects) with data processing and analysis: cleaning data, working with text corpora, or building basic pipelines.
Comfort working with APIs and integrations, such as REST endpoints, webhooks, or SDKs that connect different systems together.
Interest or experience with CRM systems, ideally Salesforce, or motivation to quickly learn how CRM platforms structure data, workflows, and automations.
Basic understanding of databases (SQL or NoSQL) and how application backends store and retrieve information.
Ability to work as part of a scrum / agile team: breaking work into increments, participating in ceremonies, and delivering iteratively.
Strong communication skills, especially when working with both technical and non-technical stakeholders (Customer Care agents, product experts, developers, and leaders).
Curiosity and a practical mindset: you enjoy experimenting, measuring results, learning from failures, and improving the solution step by step.
Attention to detail and a sense of responsibility when working with customer-facing content and sensitive data.

Responsibilities

Work with our Technical Support, Customer Care, Digital Excellence teams to understand how customers interact with support today and identify high-impact opportunities to automate or augment these workflows with AI.
Help train, and iteratively improve Taika’s behavior for support use cases, including: Curating and structuring training data from historical Tier 1 tickets, FAQs, knowledge bases, and product documentation.
Defining intents, entities, and taxonomies specifically for basic Tier 1 technical cases (e.g., configuration questions, common error patterns, standard troubleshooting steps).
Evaluating and refining prompts, retrieval strategies, and response patterns to improve accuracy, safety, and explainability.
Exposure to the backend for Taika, including: Have basic knowledge of RESTful APIs that communicate between our CRM, internal services, and the AI components.
Working with logging, monitoring, and feedback loops so that AI responses can be audited, evaluated, and continuously improved.
Contribute to integrating AI capabilities into Salesforce CRM workflows (and potentially other platforms), such as: Drafting Tier 1 case responses, suggested next steps, and troubleshooting flows for Customer Care agents.
Auto-summarizing cases, extracting key entities, and recommending knowledge articles.
Exploring UI/UX improvements that make AI assistance easy and safe for agents to use within their daily tools.
Participate in service scrums (stand-ups, sprint planning, reviews, retrospectives) with the Digital Excellence team and other stakeholders, practicing modern agile ways of working.
Collaborate closely with Customer Care and technical support experts to validate AI outputs, gather feedback, and iteratively tune the system so that it truly helps them in their day-to-day work.
Document your designs, experiments, and learnings so that future teams can build on your work and extend the AI assistant into new domains and tools.