Autodesk
SeniorGrowthSoftwareEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Growth Software Engineer at Autodesk. Skills: Growth Engineering, AI acceleration, Experimentation. Design experiments. Build experiments”
What You'll Achieve.
Drive user growth; Drive commercial outcomes; Improve key business metrics
Industry & Context.
Root cause analysis; Data-driven decisions; Troubleshooting
What They're Looking For.
Must Have
Experience with data-driven development, A testing methodologies, Iterating based on user behavior data, Experience across modern frontend frameworks, Experience across large-scale systems, Experience across cloud computing, Comfort using modern AI tools
Nice to Have
Prior experience in a formal Growth Engineering role
What You'll Do.
Improve user adoption
Improve user engagement
Execute monetisation experiments
Build minimum viable features
Analyze experiment results
Leverage AI to multiply output
Use AI tools to accelerate workflow
How You'll Work.
Team & Collaboration
Product Managers; Designers; Data Analysts; Marketing
Communication Scope
Product-minded communication
Process & Methodology
Roadmap planning
Full Job Description
**Job Requisition ID #** 25WD92032 **About the Role** We are searching for a strong Growth-focused Software Engineer to our Product Growth team driving user product adoption, engagement and monetisation for our next-generation, AI-powered architecture design product, Forma. In this role, you will sit at the critical intersection of engineering, product, and business strategy. We operate with a strong commercial bias: we believe that code is a means to an end. Your true measure of success will be the tangible commercial outcomes and user growth you drive. If you are passionate about moving the needle on key business metrics, running rapid experiments, and focusing relentlessly on the end result, this is the perfect role for you. **Responsibilities** * Drive growth: You will design, build, and deploy experiments aimed at improving user adoption and engagement as well as our early self-serve monetisation experiments. * Execute rapid experimentation: Formulate hypotheses and execute A/B tests at a high velocity. You will build minimum viable features to validate ideas quickly, understanding that many tests will fail, and that this failure is a celebrated and necessary part of the discovery process. * Collaborate cross-functionally: Work seamlessly with Product Managers, Designers, Data Analysts and Marketing to identify growth bottlenecks and brainstorm innovative, high-impact solutions. * Make data-driven decisions: Analyze experiment results and user data to uncover hidden insights. You will constantly ask "Why?" to understand user behaviour and inform your next set of technical and product decisions. * Practice pragmatic engineering: Make smart trade-offs between engineering perfection and speed to market. You will handle edge cases pragmatically, often finding creative solutions that require minimal engineering effort to validate a concept. * Leverage AI to multiply output: Act as an AI-accelerated generalist. You will use modern AI tools to accelerate your workflow
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