• Lead technical direction and work with business, AI agents and automation capabilities, and IT partners to evaluate and propose solutions • Collaborate with business and IT leadership to develop and communicate long-term vision and comprehensive strategic plans for solution architecture and delivery. • Work with product owners, business users, and technical leads to define requirements, assess business value, and develop specifications for enterprise solutions. • Drive engineering practices and delivery standards within Agile teams • Define, document, and govern application architecture, integrations, and interfaces • Drive standards for development and design techniques used by enterprise application teams. • Monitor emerging trends in enterprise application platforms and determine relevance and impact • Design and develop integrated business solutions that interact between multiple enterprise platforms within the cloud (Azure).

• Develop and execute CFD models for data center and similar built-environment applications, including interior and exterior analyses. • Perform model setup, troubleshooting, and validation with guidance from senior engineering staff. • Interpret CFD results and communicate findings through written reports and presentation materials. • Collaborate with engineering teams to support design decisions and improve system performance. • Participate in client discussions and presentations, explaining results and recommending solutions. • Apply understanding of ambient conditions, wind rose analysis, and psychrometrics to modeling efforts. • Coordinate with other Olsson teams, professional staff, and clients to support project delivery. • Periodically support CFD efforts in other markets served by Olsson, as needed. • Travel occasionally to job sites for observation or client meetings.

• Define, maintain, and govern event tracking architecture and taxonomy across web, mobile, CRM, and backend systems • Ensure consistent and reliable event tracking across all customer touchpoints • Improve funnel visibility from install through repeat transaction • Monitor, debug, and reconcile discrepancies between backend transactional data and analytics tools • Own implementation, governance, and ongoing optimisation of AppsFlyer and mobile attribution infrastructure • Improve attribution accuracy across paid and organic channels • Establish reliable and trusted channel performance reporting • Eliminate blind spots in acquisition and activation measurement • Maintain source attribution consistency across acquisition, lifecycle, and reporting systems • Design and maintain growth data pipelines and warehouse integrations across PostgreSQL, Segment, Mixpanel, Customer.io, AppsFlyer, Firebase, Power BI, and future warehouse infrastructure • Own source-of-truth consistency and reliable syncing across transactional systems, analytics platforms, CRM platforms, warehouses, and reporting environments • Ensure data quality and consistency across all connected platforms • Partner with Engineering and Data teams to improve data accessibility and reliability • Build and maintain internal growth tooling used by Marketing, Lifecycle, Commercial, and Operations teams • Enable and maintain lifecycle event triggers and CRM automation architecture within Customer.io • Own push notification infrastructure including Firebase FCM migration, token management, delivery reliability, and in-app messaging • Monitor and improve push notification delivery, open rates, token health, and engagement performance across Android and iOS • Ensure real-time data availability for lifecycle campaigns and segmentation • Improve deep-linking reliability across web and mobile • Improve lifecycle orchestration across onboarding, activation, engagement, retention, and reactivation journeys • Build and iterate on referral systems, rewards and gamification infrastructure, and onboarding flows • Develop activation nudges, lifecycle triggers, and engagement features directly within the product • Ship and test growth features quickly in close collaboration with Product and Design teams • Support implementation of loyalty and retention systems including Juice Points • Build and maintain A/B testing infrastructure, feature flagging, and experimentation frameworks • Enable rapid testing across onboarding, activation, lifecycle, referral, and retention programmes • Improve experimentation velocity across Growth and Product teams • Establish best practices for measurement, experimentation, and learning loops • Own technical visibility and reporting across Install, Signup, KYC, First Transaction, and Repeat Usage • Identify friction points and collaborate with Product and Growth teams to improve conversion performance • Improve visibility into customer drop-off points, behavioural patterns, and conversion opportunities

Role Description As a Fullstack Software Engineer, you will own meaningful parts of the product from design through deployment. This role is best suited to an engineer who enjoys moving across the stack, making product decisions, and shipping quickly in an early-stage environment. - Build and launch customer-facing AI product features - Develop modern web applications using React and TypeScript - Build backend services and APIs using Python and TypeScript - Design relational data models using PostgreSQL - Integrate large language models, third-party APIs, and customer data sources - Deploy and operate production services using AWS - Improve application performance, reliability, observability, and security - Work closely with founders, product leaders, designers, and customers - Own projects from initial problem definition through production - Help establish engineering standards as the team grows Qualifications - Approximately 1–9 years of professional software engineering experience - Strong production experience with Python, TypeScript, or both - Experience building web applications with React or NextJS - Experience developing APIs, backend services, and database-backed applications - Familiarity with PostgreSQL or another relational database - A track record of independently shipping meaningful product features - Strong product judgment and attention to user experience - Comfort working across multiple layers of a technical system - Ability to operate effectively in a fast-moving and sometimes ambiguous environment - Clear written and verbal communication - Equivalent experience matters more than a specific number of years Requirements - Nice to have: - Experience building AI, LLM, agent, or machine-learning products - Experience with AWS, GCP, Docker, Kubernetes, or Terraform - Familiarity with LLM evaluations, retrieval, prompting, or observability - Previous experience at an early-stage or venture-backed startup - Experience owning a product or technical area with limited supervision Benefits - Build production AI products used by real customers - Work on problems that span product, engineering, data, and AI - Have significant ownership over what gets built and how - Work directly with company leadership and customers - Join an early team where individual contributions have visible impact - Receive a competitive salary and meaningful equity