Technical Lead – AI Product

November 25

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Genestack

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Biotechnology • Artificial Intelligence • SaaS

Genestack is a company that specializes in making scientific data liquid and actionable for life science R&D. Their platform, the Open Data Manager (ODM), accelerates discoveries by cataloguing, curating, and harmonizing complex life science data. Genestack offers seamless integration within IT architectures, allowing for efficient data management and compliance with regulatory frameworks. They provide tools for analytical search and integration, enabling large-scale queries across life science data using well-documented APIs. Genestack also focuses on the use of AI and Large Language Models (LLMs) in life sciences to enhance research and development. The company is known for helping organizations reduce time to market and improve the return on investment from their data assets.

51 - 200 employees

🧬 Biotechnology

🤖 Artificial Intelligence

☁️ SaaS

📋 Description

• Design and implement LLM-based features into our applications using modern AI frameworks and methodologies, including RAG and agentic workflows. • Work across the AI lifecycle — from rapid prototyping to robust production systems — validating ideas and ensuring they meet real-world performance standards. • Explore and evaluate emerging AI tools and technologies (both proprietary and OSS), recommending and integrating those that bring meaningful impact. • Collaborate cross-functionally with product, data, and bioinformatics teams to ensure AI solutions are useful, performant, and aligned with scientific needs. • Ensure reliability and efficiency of AI applications, including optimization of model outputs, latency, token usage, and system robustness in production. • Evaluate and integrate open-source models, tools, and frameworks when appropriate, ensuring they meet production-quality standards. • Implement and optimize LLM model serving/tuning pipelines for scalable deployment. • Contribute to prompt design and evaluation strategies, helping to mitigate risks like hallucinations and overconfidence in real user environments. • Provide technical leadership and mentoring for engineers contributing to AI features, fostering shared learning and best practices.

🎯 Requirements

• 6+ years in software development, with a strong foundation in computer science principles, data structures, and algorithms. • Ability and motivation to rapidly learn and apply AI frameworks and workflows to production environments • Track record of technical leadership (design/architecture reviews, mentoring, cross-team alignment) — AI-specific production history not required. • Excellent skills in Python and a solid understanding of Java, enabling seamless integration of AI components into existing systems. • Familiarity with LLM APIs from various vendors (e.g., OpenAI, Anthropic) and frameworks like LangChain or LlamaIndex — prior production deployment is welcome but not strictly required. • Conceptual understanding of vector databases, retrieval pipelines, and semantic search; practical exposure (PoCs, prototypes, hack projects) is welcome, and production experience is a plus, not a must. • Working knowledge of agentic execution patterns and prompt engineering principles — able to reason about trade-offs and guide implementation even if not previously shipped to production. • Ability to evaluate open-source models, tools, and frameworks and outline integration paths; direct production integrations are optional. • Exposure to (or readiness to quickly learn) LLM model serving/tuning (e.g., vLLM, TGI, Triton). • Genuine interest in applying AI technologies to advance bioinformatics and contribute to life science innovations. • Strong ability to convey complex ideas clearly and collaborate effectively within a team. • Excellent verbal and written communication skills in English.

🏖️ Benefits

• international team of professionals • fully paid sick leaves • onboarding and domain training for newcomers • flexible work schedule