• Performs and oversees civil engineering work, focused on site design components including site layout, yard piping, paving and grading, and stormwater infrastructure • Performs and conceptual and preliminary design activities including site visits, fieldwork, alternatives analysis, and report preparation • Completes detailed design calculations, drawings, and specifications for site civil aspects of residential or commercial sites • Conducts stormwater hydraulic calculations and/or modeling and incorporates into the site civil design • Prepares and reviews technical memoranda, reports, and electronic deliverables • Reviews contractor submittals for conformance with contract drawings and specifications • Provides, and coordinates engineering services during construction • Serves as civil engineer for large multi-discipline projects

Role Description Our customer is in the middle of a deliberate shift from manual, spreadsheet-based operations to purpose-built web tools, and this contract sits right at the center of that work. They have already clearly defined the problems, designed the logic, and in several cases, already have working prototypes ready. What they need is an experienced Full-Stack Engineer to take those designs and prototypes to production-grade web applications. The work spans several interconnected systems: - Real-time train tracking and delay management - Crew scheduling analytics - Automated guest seating allocation - Shift equity monitoring Where appropriate, these tools will be enhanced with LLM-powered features (using API calls to models like Claude or DeepSeek) to automate narrative outputs, handle exceptions, and surface plain-English insights from structured data. This is a hands-on individual contributor role. You will work directly with operations leadership, not through layers of project management. The person in this role needs to move fast, communicate clearly about trade-offs, and build things that real operations teams can rely on under pressure. 📅 Start date: ASAP 🖋️ Contract type: Full-time, Contractor, 4 months with possibility of renewal/extension 🕘 Work hours: Monday to Friday, 8 AM to 5 PM PST 💻 Work mode: 100% remote from LATAM Qualifications - +6 years of professional experience in Full-Stack Web Development. - Backend: Strong expertise in Python, C#, and/or Node.js. - Frontend: JavaScript/TypeScript and Next.js/React. - Databases: Solid experience with relational databases (PostgreSQL preferred), designing schemas, writing queries, and managing migrations. - Integrations: Proven experience handling REST APIs (auth, pagination, rate limits) and LLM APIs (prompt engineering, structured outputs, context management). - Cloud Basics: Ability to deploy and host applications on cloud platforms (Azure preferred) without a dedicated DevOps resource. Requirements - Experience migrating Excel/VBA logic to web applications. - Familiarity with scheduling or workforce management system APIs (Connecteam, Workforce.com, Deputy, etc.). - Background building operations-facing tooling or working in rail, transit, hospitality, or tour operations environments. - Experience with real-time or near-real-time data display (websockets, SSE, or polling). - Familiarity with Microsoft Graph API / Microsoft 365 integrations or data visualization libraries. - Comfort working from a functional spec rather than a fully detailed technical design. Benefits - 💻 100% remote from anywhere in LATAM - 💸 Competitive compensation in USD - 🌍 Work with global teams and top-tier clients - 🫶 People-first culture built on trust, autonomy, and impact Company Description Launchpad Technologies Inc. is a global technology partner connecting top talent with high-impact projects across North America and beyond. We specialize in Staff Augmentation and product development, helping companies scale with agility while empowering professionals to grow in meaningful, remote-first environments.

Role Description As a Senior ML Engineer at NineTwoThree AI Studio, you will sit at the intersection of production-grade software engineering, advanced natural language processing, and client delivery. We build custom, high-impact AI systems for brands and startups across diverse industries (such as healthcare, logistics, and fintech). Instead of siloed academic research, this role demands a product-minded builder. You will design, optimize, and deploy robust LLM applications, custom predictive analytics, and agentic workflows directly into our clients' software ecosystems, taking absolute ownership of features from prototype to production. Responsibilities - Architect & Build AI Features: Design and implement robust classical ML and generative AI solutions, striking the right balance between autonomous agentic architectures and deterministic pipelines. - Evaluate: Design and maintain evaluation frameworks to measure AI quality, reliability, safety, and business impact before and after deployment. - Integrate & Deploy: Partner closely with full-stack developers and DevOps to seamlessly integrate AI capabilities into client web and mobile applications using serverless architecture (e.g., AWS Lambda) or API endpoints. - Optimize for Production: Refine prompts, system instructions, and chunking strategies to balance accuracy, latency, token consumption, and data privacy. - Traditional Predictive Analytics: Clean and process unstructured or historical client data to train/fine-tune custom algorithms for specific business problems (such as forecasting, classification, or anomaly detection). - Collaborate & Communicate: Actively participate in client discovery sessions, translate ambiguous business requirements into viable technical scopes, and demo prototypes directly to stakeholder teams. - Maintain Engineering Excellence: Engage in constructive code reviews, implement rigorous validation patterns to test AI outputs, and contribute templates or runbooks to our internal AI knowledge base. Qualifications - Proven Track Record: 3+ years of experience engineering software with a strong focus on machine learning and natural language processing. - LLM & Generative AI Mastery: In-depth understanding of modern LLM architectures, context window mechanics, semantic search techniques, and the limitations of generative systems. - Production experience: Experience building and operating production AI systems, including monitoring, evaluation, debugging, and iterative improvement. - Evaluation experience: Understanding of evaluation methodologies for LLM-based systems, including retrieval quality, hallucination detection, and task-specific performance measurement. - Python & SQL Proficiency: Exceptional Python coding skills and the ability to query, clean, and structure data efficiently. - Cloud Infrastructure: Hands-on experience deploying ML or API services within cloud ecosystems, preferably AWS. - Ownership: Comfortable taking ownership of ambiguous problems from initial discovery through production deployment and ongoing support. Product & Team Capabilities - Ambiguity to Execution: Ability to drop into a completely new industry vertical, understand its data constraints, and spin up a working proof-of-concept within a few weeks. - The "Product Engineer" Mindset: Passion for seeing things ship and understanding why something is being built from a business value standpoint, not just what is being built. - Communication: Fluent written and spoken English. Comfortable interacting with client stakeholders and breaking down technical workflows into clear concepts. - Adaptability: Eagerness to experiment with and evaluate fast-emerging AI development tools, models, and frameworks. - Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent practical experience). Benefits - Annual paid vacation: 20 days off per year during the first 3 years, increasing to 25 days in later years. - Paid sick leave, 10 national holidays, and 2 company days off. - Well-being budget. - Health Insurance allowance. - Maternity/paternity leave. - Reimbursement of expenses for professional development courses and certifications (up to 100% in agreement with Manager). - Hardware upon business needs. - Strong positive engineering culture, a tightly-knit team of professionals with a good sense of humor. What's The Process We value your time and ours and make the process fast and easy. Our interview process takes the following steps: a short interview with the HR, 2nd technical interview with ML Engineer and CTO (optional), 3rd live-coding interview, Offer.

Role Description Tangible Markets builds secondary-transaction infrastructure for private markets. Our clients are banks, fund administrators, and secondaries teams whose workflows are technical, regulated, and specific. You sit between them and our product engineering. The role blends solutions engineering with customer success, plus real engineering work. You lead technical discussions with clients, shape how the platform fits their workflow, own their success after go-live, and help build configurations and integrations that close the gap. You are not embedded on client sites full-time, and this is not a pure relationship role either. Most weeks split between client-facing work and hands-on technical work. Full-time · Remote (European time zones preferred) Tasks - Client-facing (roughly half the role) - Run technical discussions during onboarding: architecture reviews, security questionnaires, SSO and data-flow conversations with client IT teams - Translate client workflow requirements into product terms, and product capabilities into client terms - Own accounts after go-live: adoption, expansion, the quarterly “how is this actually going” conversation - Be the trusted technical contact when something breaks or a new requirement lands - Product and engineering (the other half) - Help build client-specific configuration, integrations, and glue code (SSO, data mappings, API integrations, etc.) - Turn recurring client asks into structured product requirements and argue for them with the product team - Prototype solutions fast, validate them with the client, then hand the generalizable parts to the engineering team - Write the runbooks and docs that make each client’s setup maintainable by someone other than you Qualifications - 3+ years in a technical role with client exposure: solutions engineering, sales engineering, technical account management, or product engineering with heavy customer contact. - You can read and write production code: You don’t need to be the strongest or only engineer on the team, but “I’ll build it” has to be a real option, not a handoff. - You can hold a room: an SSO deep-dive with a bank’s IT security team in the morning, a product feedback session in the afternoon. - Financial services background, or evidence you absorb regulated domains fast. - You write clearly: Requirement docs, runbooks, and follow-up emails carry most of this job’s leverage. - Judgment about what to build, what to configure, and what to push back on. Requirements - Nice to have: - Anything fintech, especially on the vendor for banks (or other fintechs) side. - Prior work at an early-stage B2B company where you wore several hats. - Familiarity with enterprise security and compliance processes (vendor due diligence, DORA, GDPR). - What this role is not: - Not pre-sales quota-carrying. You join conversations for technical depth, not to close. - Not full-time on-site embedding. Client contact is regular but structured: calls, workshops. - Not a support queue. You own outcomes for accounts, not tickets. Why this role matters Enterprise clients in private markets churn because nobody on the vendor side understood their workflow well enough to make the platform fit. This role exists so that someone does, and so that what they learn changes the product. Process - 30-minute intro call - Technical conversation around a real (anonymized) client scenario - Working session: scope a solution and present it back - Conversation with the founders Company Description Tangible is transforming the way secondary markets work for LPs, GPs and wealth managers. We combine technology and deep private markets expertise to bring transparency, efficiency and simplicity to secondary transactions. Our products enable more LPs to sell on the secondary market and empower GPs and wealth managers to create scalable liquidity solutions for their investors.