Full Stack (AI) Developer (Talent Pool)

Viseven Group is a leading global B2B MarTech service provider, empowering Pharma and LifeScience companies since 2009. Our mission is to drive digital transformation and excellence, offering comprehensive end-to-end software and digital marketing services tailored to the pharmaceutical industry. The company's solutions, products, and services are actively used by the top 100 Pharma and Life Science companies. At Viseven, our rapidly growing team boasts over 700 highly skilled professionals, including experts in development, design, business analysis, project management, delivery, sales, marketing, and customer success. With a global footprint in more than 30 countries across the US, LATAM, Europe, and APAC, and physical offices in Ukraine, Poland, Estonia, India, and the US, we are well-positioned to serve our diverse clientele. Join us and become part of a pioneering team dedicated to shaping the future of digital transformation in Pharma and Life Sciences across more than 50 countries around the globe. Responsibilities: As a Middle Full stack Engineer, you'll work on well-scoped tasks of moderate complexity, with guidance and code review from senior engineers, contributing to larger AI initiatives owned by the team. - Develop and integrate AI agents with tool-use, memory, and context management, leveraging LangChain, LangGraph, and LangSmith frameworks, and integrating with foundational Large Language Models (LLMs). - Integrate LLMs with external tools, APIs, knowledge sources, and enterprise systems. - Contribute to building retrieval layers (e. g. , hybrid search, vector search, metadata filtering) optimized for LLM consumption. - Stay up to date with modern technologies and best practices for building Gen AI-based applications.

Required skills & knowledge: - Proficiency in TypeScript and Node. js. - Good understanding of software design principles, design patterns, and modern development best practices. - Experience with NoSQL databases; familiarity with vector databases (OpenSearch a plus). - Familiarity with AI agent workflows (tool-use, memory, and context management), or a strong interest in building them. - Basic understanding of agentic behaviors and patterns, such as planning, retrieval, and self-correction. - Exposure to LangChain and/or LangGraph libraries (or a strong willingness to ramp up quickly). - Understanding of RAG workflows; hands-on experience is a plus. - Familiarity with evaluation and testing approaches for AI systems. Nice to have: - Experience working with a microservices-based architecture. - Experience with AWS (S3, Lambda, ECS, Bedrock). - Experience with Docker & Kubernetes. - Python knowledge.