Role Description We're looking for a Forward Deployed Engineer who owns customer outcomes, not just code. This is a hybrid role combining software engineering, AI, data engineering, product thinking, and customer collaboration. You'll work directly with enterprise customers, build production-grade integrations and AI workflows, rapidly deliver proof-of-concepts, and turn customer needs into scalable platform capabilities. If you enjoy solving ambiguous problems, building production systems, and seeing your work create immediate business impact, you'll thrive here. What You'll Do - Customer Delivery: - Own enterprise customer implementations from discovery through production deployment - Work directly with customer teams to understand business challenges and define technical solutions - Build production-ready AI workflows, integrations, and data pipelines - Product Engineering: - Develop scalable integrations, APIs, automations, and AI-powered workflows - Build features that initially solve customer-specific needs before evolving into core platform capabilities - Continuously improve platform scalability through automation - Data & AI: - Design and implement data pipelines and integrations - Build evaluation frameworks for AI systems - Ensure outputs remain explainable, reliable, and production-ready - Customer Success: - Build rapid Proofs of Concept (PoCs) for enterprise prospects - Help customers achieve measurable ROI quickly - Translate technical concepts into business value for non-technical stakeholders Qualifications - 5+ years of software engineering experience - Strong Python and SQL skills - Experience building production software end-to-end - Strong data engineering background (ETL, pipelines, data integrations) - Customer-facing experience working directly with enterprise clients - Excellent communication and stakeholder management skills - Comfortable working independently in ambiguous environments - Strong ownership mindset with a focus on customer outcomes Requirements - Nice to Have: - Forward Deployed Engineer, Customer Engineer, Solutions Engineer, or Product Engineer experience - Experience with Databricks, Spark, Snowflake, or dbt - Experience building AI/LLM applications (LangChain, LangGraph, RAG, Vector Databases) - Startup or founding engineer experience - FinTech or enterprise SaaS background Benefits - Competitive salary - Meaningful equity - Fully remote work within the European Time Zone - Employer of Record (EOR) employment - High ownership and direct customer impact - Opportunity to work with cutting-edge AI technologies - Collaborative, high-performance engineering culture - Career growth in one of Europe's fastest-growing AI fintech companies

Role Description The Sr. Software Engineer II - AI will lead the build of GenAI-powered product experiences and the shared AI platform infrastructure that powers them. This includes: - RAG pipelines over the iHerb catalog and customer reviews - LLM-driven personalization - A conversational Wellness Agent - Agentic workflow systems - The evals and MLOps layer that makes AI features production-grade and repeatable Specializations within this track include: - RAG and personalization - Agent framework and tool use - Evals and guardrails - LLM application development for internal business functions such as marketing automation and BI agents Qualifications - AI-driven SDLC: hands-on experience shipping production code with AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor - Full-stack awareness: comfortable contributing across layers of the stack - Production ownership: experience owning features end-to-end from spec through deployment - Code quality fundamentals: strong grasp of software design principles, automated testing, code review, and CI/CD - Fully autonomous; drives technical decisions within the team; mentors junior engineers - Python proficiency; comfortable building and operating production LLM applications - Hands-on experience with at least one specialization: RAG and retrieval systems, LLM evaluation, agentic frameworks, or LLM-based workflow automation - Understanding of prompt engineering, context window management, and LLM output quality tradeoffs - Familiarity with vector databases, embedding models, or semantic search - High degree of accuracy and attention to detail - Excellent organization skills and ability to multi-task Requirements - Generally requires a minimum of 10+ years of software engineering experience - Bachelor’s Degree in Computer Science or related field preferred, or a combination of education and equivalent work experience Benefits - The expected salary range for this role is $187,000.00 - $235,000.00 USD - The actual base pay offered will be determined by factors such as the candidate's relevant experience, education, geographic location, and internal equity Physical Demands The physical demands described here are representative of those that must be met by a Team Member to successfully perform the essential functions of this job: - Regularly required to talk and hear - Frequently required to sit, walk, climb stairs, use hands and fingers, bend, stoop and reach with hands and arms - Occasionally lift or move office products and supplies up to 25 pounds Work Environment - The noise in the work environment is usually moderate - Hectic, fast-paced with multi-level distractions - Professional, yet casual work environment - Office / Warehouse environment - Ability to work extended hours as required

• Build the features • Full-stack on AWS and Azure using Claude and other models • Work with users • Sit with the business day to day and build with them • Keep quality up • Tests and evaluations on everything that ships • Take design direction from the Solution Architect

• Work closely with customers, product partners, and team members to understand workflows, clarify requirements, and translate needs into well-scoped technical deliverables. • Build applied AI capabilities across high-value enterprise workflows such as automation, document intelligence, decision support, fraud intelligence, and intelligent assistants. • Implement context-aware agentic systems that orchestrate tools, APIs, reasoning steps, and business logic using established architecture patterns • Identify when existing agents, models, APIs, or platform capabilities can be reused and contribute to practical build vs. reuse recommendations. • Stay current on practical AI engineering patterns and bring forward ideas that improve quality, speed, or customer value. • Design and develop software and improve existing code to make it more efficient to detect bugs in the code • Write unit-tests and validate your software against acceptance criteria • Author, apply and advocate for team coding, documenting and testing standards • Conduct impact analysis to proactively identify impact of a change across multiple applications • Learn the business process domain to better support the business • Experiment and test ideas, validate assumptions against needs, reach conclusions and recommend solutions • Lead code reviews and communicate application changes • Document code and projects so others can easily understand, maintain and support • Debug the problems which arise in production and propose effective solutions within the application and across multiple applications • Read, write and review design documents • Contribute to team's sprint commitments and actively participate in our Agile practices • Lead continuous learning activities to improve design and code quality as well as to increase application domain knowledge • Participate in the talent selection process • Guide and review the code, designs and documentation of less experienced software engineers