Lead Generative AI Engineer (AWS Bedrock & LLMs)

Space Inventive is an innovative and dynamic company that specializes in leading businesses through transformative journeys in the digital era. They are pioneers in driving innovation and helping organizations transition into digitally mature entities. With a wide range of cutting-edge services, including web enterprise application development, AI & ML development, cloud engineering, data engineering, and business intelligence, Space craft's tailor-made solutions to meet each client's unique challenges. Their integrated approach combines strategic vision with digital expertise, empowering businesses to create new models, modernize legacy systems, and launch market-ready digital products and platforms.

: We are seeking an experienced Generative AI Lead/Senior Developer to design, develop, and implement enterprise-scale AI solutions leveraging Amazon Bedrock, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) frameworks.

involves building innovative AI-powered applications such as chatbots, copilots, knowledge assistants, and intelligent document processing solutions while driving the adoption of Generative AI across business functions. The ideal candidate will have strong expertise in AWS cloud technologies, GenAI platforms, prompt engineering, LLM integration, and API-driven architectures, with the ability to translate business

into scalable, secure, and high-performing AI solutions. This position requires a hands-on technical leader who can collaborate with cross-functional teams, ensure responsible AI practices, and deliver enterprise-grade GenAI solutions aligned with security, governance, and compliance standards. Lead Generative AI/Senior Developer • Design and build GenAI solutions using Amazon Bedrock/similar GenAI Platform, including: • Integration with foundation models (Anthropic Claude, Titan, etc.) • Prompt engineering and optimization • RAG (Retrieval Augmented Generation) architectures • Develop AI-powered applications such as chatbots, copilots, knowledge assistants, and document processing solutions. • Evaluate and fine-tune LLM-based use cases for business scenarios. • Integrate GenAI models with enterprise applications and APIs. • Implement secure AI architectures aligned with enterprise and regulatory standards. • Ensure data privacy, model governance, and responsible AI practices.