About the Company

Quantanite is a global customer experience and digital solutions partner that blends cutting-edge AI with the human touch. Headquartered in London and operating across four continents, our 2,000-strong team helps some of the world's fastest-growing brands scale smarter, work faster, and deliver better serviceevery time. We are dedicated to delivering great service built on smart technology and smarter people. Through proprietary AI tools like MBIUS and a collaborative culture, we empower our teams with the tools, training, and trust necessary to make a significant impact. If you are looking to be part of a forward-thinking, fast-moving, and inclusive global team that values both results and relationships, Quantanite is the place for you.

About the Role

This highly visible Senior role is essential for driving our next generation of digital transformation solutions, specifically within our Business Process Outsourcing (BPO) operations serving a diverse portfolio of international clients. The Senior Generative AI Engineer will architect and lead the development of production-ready, multi-agent systems, advanced chatbots, and intelligent automation tools by leveraging state-of-the-art Large Language Models (LLMs) to address complex, high-impact business challenges.

Responsibilities

The Senior Generative AI Engineer will take ownership of the full lifecycle of AI solutions, from strategic conceptual design to production monitoring and performance optimization.
Strategic Solution Design and Deployment: Architect, design, and launch high-impact Generative AI solutions, focusing on the development of complex, multi-agent architectures utilizing foundational models such as GPT, LLaMA, or Claude.
Model Optimization and Refinement: Oversee and execute precise fine-tuning of models using proprietary company data to significantly enhance domain-specific accuracy and overall performance for global client needs.
Advanced Prompt Engineering and Guardrails: Strategically craft and rigorously optimize advanced prompt engineering strategies to maximize model efficacy, establish technical guardrails to mitigate risks such as AI hallucination, and manage systemic bias in deployed models, ensuring ethical and safe AI usage.
System Integration and Scalability: Define and manage the seamless integration of sophisticated AI models into various enterprise systems, including web applications and high-availability APIs, ensuring robust and scalable deployment across international BPO operations.
RAG Architecture Leadership: Architect and implement robust Retrieval-Augmented Generation (RAG) pipelines utilizing advanced vector databases to enrich model context, improve grounding, and solve specific client knowledge-retrieval challenges.
Performance Monitoring and Optimization: Lead the continuous monitoring, performance tuning, and cost-efficient operation of deployed models in a demanding production environment.
Leadership and Mentorship: As a Senior Engineer, you will play a crucial role in shaping the team's technical direction and fostering growth.
Technical Direction and Roadmapping: Define the technical roadmap, establish best practices, and drive critical architecture decisions for the Generative AI team, ensuring alignment with organizational goals.
Cross-Functional Collaboration: Serve as the primary technical driver and subject matter expert, partnering closely with product and engineering teams to translate high-level business requirements from international clients into functional, high-quality AI technology.
Mentorship and Coaching: Actively mentor junior engineers and team members, conducting code reviews, sharing knowledge on advanced GenAI techniques, and fostering a culture of technical excellence.
Project and Task Management: Take ownership of complex projects, delegate tasks to junior collaborators, and ensure project milestones are met on time and to a high standard.
Communication: Clearly articulate complex AI concepts, strategic project statuses, and technical risks to both technical and non-technical executive stakeholders.

Qualifications

Minimum 5+ years of progressive experience in AI/ML engineering, with at least 2 years focused specifically on Generative AI.
Extensive previous experience in building, deploying, and managing conversational AI and assistant bots in a high-traffic production environment.

Required Skills

Core Programming: Expert proficiency in Python is essential; familiarity with enterprise-level programming languages and best practices is required.
LLM and NLP Expertise: Deep theoretical and practical understanding of Large Language Models (LLMs), transformer model architectures, and state-of-the-art Natural Language Processing (NLP) techniques.
AI/ML Framework Proficiency: Hands-on expertise with major AI/ML frameworks such as PyTorch, TensorFlow, or Hugging Face.
Generative AI Lifecycle: Proven capability in advanced prompt engineering, comprehensive model fine-tuning, and managing the overall GenAI development lifecycle.
Framework Utilization: Extensive experience with orchestration frameworks like LangChain or LlamaIndex.
Vector Database Familiarity: Working knowledge of scalable vector databases, including Pinecone, FAISS, Weaviate, or Chroma.
Cloud Platform Experience: Proven experience deploying and managing highly available, low-latency services on major cloud providers (AWS, Azure, or GCP).
System Architecture: Solid grasp of designing highly available and scalable systems, including implementing robust REST and/or GraphQL APIs.

Preferred Skills

Experience developing and experimenting with multimodal models (text, images, audio).
In-depth knowledge of MLOps principles and practices for the real-world deployment, monitoring, and continuous management of machine learning models.
Demonstrated in-depth awareness of data privacy regulations, international compliance standards, and AI ethics.
Proven record of successfully leading the launch of a production-grade conversational AI solution or copilot.

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