Iris.ai

• Own the full development lifecycle — from idea to architecture, implementation, testing, and delivery of real-world AI products • Design and build robust AI systems, including Iris.ai ’s proprietary Retrieval-Augmented Generation (RAG) pipelines and LLM Evaluation Frameworks used by leading R&D teams • Drive innovation by testing new approaches and bringing new AI research into production • Collaborate across teams — work closely with researchers, product managers, and fellow engineers to shape and ship powerful features • Build systems for performance and reliability, ensuring they are scalable, testable, and maintainable • Contribute to a global mission to transform how the world interacts with scientific knowledge and applied AI • Thrive in a remote-first, agile environment, contributing meaningfully within a distributed, deep-tech team • Keep learning, always — we’ll support you with space, mentorship, and resources to grow as an AI engineer

Role Description As a Senior AI Engineer at Iris.ai, you’ll join a remote-first, AI-native team focused on building production-ready systems powered by RAG, LLMs, and AI agents. You’ll collaborate with research scientists, engineers, and product managers to design and deliver AI features that go beyond generation - helping users navigate, reason, and act on complex knowledge. You’ll work across the full development lifecycle, from design to deployment, and play a key role in shaping how next-gen AI is evaluated, trusted, and adopted in real-world workflows. What You’ll Do - Own the full development lifecycle — from idea to architecture, implementation, testing, and delivery of real-world AI products - Design and build robust AI systems, including Iris.ai’s proprietary Retrieval-Augmented Generation (RAG) pipelines and LLM Evaluation Frameworks used by leading R&D teams - Drive innovation by testing new approaches and bringing new AI research into production - Collaborate across teams — work closely with researchers, product managers, and fellow engineers to shape and ship powerful features - Build systems for performance and reliability, ensuring they are scalable, testable, and maintainable - Contribute to a global mission to transform how the world interacts with scientific knowledge and applied AI - Thrive in a remote-first, agile environment, contributing meaningfully within a distributed, deep-tech team - Keep learning, always — we’ll support you with space, mentorship, and resources to grow as an AI engineer Our Tech Stack - Python & Django - Relational databases (PostgreSQL) - Non-relational and vector databases (Elasticsearch / OpenSearch, ChromaDB, Couchbase) - AI / ML / NLP libraries (Gensim, Torch, Transformers, spaCy, Autogen, etc.) - Cloud (AWS) - GenAI tools (Windsurf, Cursor, Amazon Q, Claude and others) - Git & CI / CD Qualifications - 5+ years in software development, including 3+ years with Python - Solid experience in web backends (Django/Flask), REST APIs, databases, and cloud infrastructure - Familiarity with ML systems or motivation to learn in depth - Ability to work in a remote-first, collaborative environment - Proficiency in English Any Of These Would Be An Advantage - Advanced degree in Computer Science or related field - Previous work with LLMs, NLP, or AI model evaluation - Experience contributing to or using RAG systems in production - Open-source contributions, academic research, or mentoring Benefits - 30 days paid vacation - 5 additional days paid vacation for Learning and Development - Private health insurance (premium coverage) and bi-annual health checks - Free MultiSport card or Fitness subscription coverage for your physical well-being - Remote-first & flexible hours — work where you're at your best - Personal annual learning budget for conferences, courses, or certifications - Personal equipment budget to choose the gear that suits your style - Charity and volunteer activities - Seasonal working camps (summer & winter) and team retreats - Ongoing growth through weekly tech deep dives, mentorship, pair coding, and knowledge-sharing Compensation & Ownership - Compensation that reflects your value. Our salaries are typically 25% above local market averages, ensuring competitive, fair pay across regions and roles. And we review it annually. - Stock options build wealth! At Iris.ai all colleagues receive ownership in the company, part of our ESOP pool (3%).

• Design end-to-end Agentic solutions based on Iris.ai ’s products for our Enterprise clients: design modular pipelines that combine Data Ingestion, RAG, LLM evaluation, and autonomous decision-making into cohesive workflows that bring direct value to the client. • Rapid prototyping - rapidly spin up proof-of-concepts, run benchmarks on accuracy and reasoning performance, and iterate based on real-world data with the client. • Integration and deployment - You will collaborate with the Tech team to deliver, orchestrate, and monitor AI Agents in production environments. • Engage in sessions with the Client - You will translate customer requirements into technical designs, run technical sessions with the Client, and provide best-practice guidance for AI adoption. • Collaborate in a cross-dimensional team. Work closely with sales managers, product managers, engineers, designers and researchers to align architecture with product vision and user needs. • Drive innovation by testing new approaches with the Clients and bringing new ideas to the product team. • Focus client systems on performance and reliability, ensuring they are scalable, testable, and maintainable. • Thrive in a remote-first, agile environment, contributing meaningfully within a distributed, deep-tech team. • Keep learning, always — we’ll support you with space, mentorship, and resources to grow as an AI engineer

• Own full sales cycle ownership – From first engagement to long-term success, expansion, and advocacy • Strategic prospecting - Engage with senior AI leadership and/or C-suite at target organizations through a consultative approach, understanding their strategic priorities and identifying high-value AI use cases • Work with senior AI leaders and C-suite stakeholders to uncover high-impact opportunities and shape tailored AI solutions together • Relationship building – Become a trusted advisor and foster long-term collaboration with key stakeholders across Engineering, Product, innovation, and business teams • Revenue leadership – Drive new business and expansion through sustained value creation for the region • Go-to-market execution – Shape sales playbooks and partnership models, campaign priorities with support demand-gen and marketing teams. • Sales Engagement - Lead complex proposal development, solution presentations, and commercial negotiations in collaboration with the pre-sales engineering team. • Sales ops excellence – Maintain CRM hygiene, monitor pipeline health, and leverage data to optimize conversions. • Market intelligence – Feed insights back to marketing and product to sharpen ICP definition and value messaging

• Design, implement and deliver scalable AI-driven software systems using Python. • Drive innovation: research, test and adopt new technologies to enhance development productivity. • Collaborate with cross-functional teams to define, design, and ship new features. • Participate in the full development cycle from specification to deployment. • Provide technical guidance and mentorship to team members, ensuring code quality and best practices. • Guide architectural decisions and ensure alignment with product strategy. • Participate in hiring, onboarding and performance reviews of engineers.

• Own full sales cycle ownership – From first engagement to long-term success, expansion, and advocacy • Strategic prospecting - Engage with senior AI leadership and/or C-suite at target organizations through a consultative approach, understanding their strategic priorities and identifying high-value AI use cases • Work with senior AI leaders and C-suite stakeholders to uncover high-impact opportunities and shape tailored AI solutions together • Relationship building – Become a trusted advisor and foster long-term collaboration with key stakeholders across Engineering, Product, innovation, and business teams • Revenue leadership – Drive new business and expansion through sustained value creation for the region • Go-to-market execution – Shape sales playbooks and partnership models, campaign priorities with support demand-gen and marketing teams. • Sales Engagement - Lead complex proposal development, solution presentations, and commercial negotiations in collaboration with the pre-sales engineering team. • Sales ops excellence – Maintain CRM hygiene, monitor pipeline health, and leverage data to optimize conversions. • Market intelligence – Feed insights back to marketing and product to sharpen ICP definition and value messaging

• Full sales cycle ownership – From qualified lead to contract signing to post-sale success • Strategic prospecting - Engage with senior AI leadership and/or C-suite at target organizations through a consultative approach, understanding their strategic priorities and identifying high-value AI use cases • Relationship building – Develop long-term trust with key stakeholders across Engineering, Product, innovation, and business teams. • Revenue leadership – Hit and exceed quarterly/annual targets for the region. Drive new logo acquisition and account expansions. • Go-to-market execution – Shape sales playbooks, campaign priorities, partnership model with support demand-gen and marketing teams. • Sales Engagement - Lead complex proposal development, solution presentations, and commercial negotiations in collaboration with the pre-sales engineering team. • Sales ops excellence – Maintain CRM hygiene, monitor pipeline health, and leverage data to optimize conversions. • Market intelligence – Feed insights back to marketing and product to sharpen ICP definition and value messaging

• Market research & prospecting – Identify target companies, industries, and key stakeholders in AI, data, and R&D teams • Lead generation support – Help build and qualify outbound lead lists and assist with outreach campaigns through a programmatic manner • Sales support – Assist in preparing presentations, proposals, and sales materials • Partnership development support -Identifying, researching, and coordinating with potential partners, and supporting ongoing partner development initiatives. • CRM management – Maintain accurate records of leads, activities, and pipeline in CRM tools • Go-to-market support – Collaborate with marketing on campaigns, events, and messaging • Customer insights – Research industry trends and help identify AI use cases across sectors • Cross-functional collaboration – Work with sales, marketing, and product teams to understand how deals are built and closed

• Full sales cycle ownership – From qualified lead to contract signing to post-sale success • Strategic prospecting - Engage with senior AI leadership and/or C-suite at target organizations through a consultative approach, understanding their strategic priorities and identifying high-value AI use cases • Relationship building – Develop long-term trust with key stakeholders across Engineering, Product, innovation, and business teams. • Revenue leadership – Hit and exceed quarterly/annual targets for the region. • Drive new logo acquisition and account expansions. • Go-to-market execution – Shape sales playbooks, campaign priorities, partnership model with support demand-gen and marketing teams. • Sales Engagement - Lead complex proposal development, solution presentations, and commercial negotiations in collaboration with the pre-sales engineering team. • Sales ops excellence – Maintain CRM hygiene, monitor pipeline health, and leverage data to optimize conversions. • Market intelligence – Feed insights back to marketing and product to sharpen ICP definition and value messaging

• Design and implement novel NLP & ML methods (from theory to code) • Run end-to-end experiments: data, training, evaluation, ablations • Translate research insights into prototypes and production features • Collaborate closely with engineers and product teams • Publish, present, and engage with the AI research community • Lead and co-author EU and national research grant proposals • Write and publish research articles