Senior Software Engineer - AI/ML

Job description

At Mitratech, we are a team of technocrats focused on building world-class products that simplify operations in the Legal, Risk, Compliance, and HR functions. We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun! Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading-edge technologies available. For over 35 years, the experts at Mitratech have been focused on solving complex needs. Today, we serve 20,000 client companies of all sizes globally, representing 30% of the Fortune 500 and over 500,000 users in over 160 countries. As we continue to grow, we’re always looking for resourceful, enthusiastic, and fresh perspectives. Join our global team and see what makes Mitratech a truly exceptional place to work! Given our continued growth, we always have room for more intellect, energy, and enthusiasm - join our global team and see why it's so special to be a part of Mitratech! Job Overview We are seeking a highly skilled Senior Software Engineer specialising in Generative AI and Large Language Models, with a strong focus on agentic systems, Retrieval-Augmented Generation, and AI evaluations, to join our dynamic team. The ideal candidate will play a pivotal role in architecting and delivering production-grade AI solutions that meet complex business objectives effectively. This position requires a blend of expertise in modern AI technologies and software engineering, along with a passion for staying at the forefront of advancements. Essential Duties & Responsibilities : Design, build, and operate multi-agent workflows and tool-enabled agents, implementing orchestration logic, state management, safety guardrails, and fallback strategies for resilient production pipelines. Architect and maintain end-to-end RAG systems, covering document ingestion, chunking, embedding, vector retrieval, reranking, and answer synthesis with a focus on quality, attribution, and latency. Evaluate and integrate LLMs and GenAI services across cost, performance, and privacy dimensions, selecting the right mix of managed and in-house models. Develop, version, and optimise prompting strategie…