Applied AI Engineer, Internal Products

BioRender is on a mission to accelerate the world’s ability to learn, discover, and communicate science. They are seeking an Applied AI Engineer to build internal, AI-powered products that enhance team effectiveness and streamline workflows across the company.

Responsibilities:

• Partner with internal teams to build high-leverage automation and AI-powered systems that meaningfully improve how work gets done
• Identify and own high-impact problems, translating business needs into well-designed internal systems and tools
• Design, build, and ship automation and AI-driven solutions using appropriate levels of engineering rigor
• Exercise sound judgment in choosing when to build, buy, or configure existing tools, and when deeper custom engineering is required
• Evolve prototypes into reliable, production-ready systems with attention to correctness, observability, and maintainability
• Embed with teams across Sales, Finance, People, Customer Success, and other functions to understand workflows, decision points, and sources of friction
• Partner closely with business and engineering stakeholders to ensure adoption, trust, and long-term value
• Document patterns, share learnings, and enable others to safely extend or build on what you create, with input into how we scale this approach across the company

Requirements:

• 4+ years of software engineering experience building and shipping production systems or internal applications end-to-end (backend + basic frontend), preferably in Python and JavaScript/Node
• Hands-on experience with AI models and APIs (e.g., OpenAI, Anthropic/Claude, Google/Gemini, v0/Vercel ecosystem) applied to real product or internal workflow problems
• Strong experience building and maintaining integrations between SaaS tools, internal systems, and third-party APIs
• High agency and builder mindset — comfortable owning ambiguous problems and moving from idea to working system
• Proactive, self-directed work style — can break down ambiguous problems, prioritize, and execute with minimal oversight
• Product-oriented thinking — ability to map and understand complex business processes, translate them into technical designs, and iterate with stakeholders
• Ability to rapidly build and test solutions, choosing the appropriate level of engineering from custom code to low-code tools
• Solid software engineering fundamentals: testing, logging, monitoring, error handling, security basics, and code quality
• Ability to communicate clearly with non-technical partners and build trust in the systems you ship
• Curiosity about how work should evolve in an AI-native world, paired with pragmatism about what's ready to deploy today
• Experience designing, building, or orchestrating AI agents or multi-step AI workflows
• Track record of automating repetitive tasks for teams using AI and/or traditional scripting
• Demonstrated experience leading AI-driven workflow transformations across multiple business units or functions
• Experience with AI SDKs and modern developer ecosystems (e.g., Vercel, Claude/Code, Google's AIStudio, Claude Agent SDK, Google Agent SDK, OpenAI Agent SDK)
• Prior work in SaaS or B2B product companies, especially in roles close to GTM, Tooling or operations
• Prior consulting or internal role focused on process optimization, workflow redesign, or digital transformation
• Prior experience as a technical founder or early engineer
• Public artifacts showing thought leadership (technical blogs, talks, videos, open-source contributions)
• Familiarity with low-code/no-code tools and RPA-style automations where appropriate (e.g. Zapier, Airflow etc)
• Basic product thinking: running experiments, A/B tests, or pilots with business stakeholders