Senior AI Engineer

Job Title: Senior Generative AI Engineer

About Quantanite

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 service—every time. We believe great service is built on two things: smart tech and even smarter people. 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.

Position Overview

We are looking for an experienced Senior Generative AI Engineer with minimum 5 Years of experience to architect, develop, and lead the deployment of complex, production-ready AI solutions. This role is responsible for the full lifecycle of AI engineering—from strategic design to end-to-end deployment—with a specific focus on multi-agent architectures, advanced knowledge retrieval, and Large Language Models (LLMs). You will drive technical innovation, mentor junior engineers, and translate complex business requirements into scalable, high-impact AI systems.

Key Responsibilities

• End-to-End Development: Own the full AI lifecycle, from conceptual design and architectural planning to model training, evaluation, and production deployment.
• Multi-Agent Systems: Architect and implement sophisticated multi-agent workflows and agentic systems using frameworks like LangChain, LlamaIndex, Langraph and OpenAI SDK to solve complex enterprise problems.
• RAG & Model Optimization: Design robust Retrieval-Augmented Generation (RAG) pipelines using vector databases and execute precise fine-tuning of LLMs (e.g., GPT, Claude, LLaMA) using techniques like LoRA/QLoRA.
• Deployment & MLOps: Ensure systems are production-ready, scalable, and secure. Implement effective monitoring, evaluation Technical Leadership: Mentor junior engineers, conduct code reviews, establish engineering best practices, and collaborate with cross-functional teams (Product, Data, DevOps) to deliver high-quality solutions.
  

Required Skills & Experience

• frameworks (e.g., LangSmith, AgentOps), and technical guardrails to mitigate hallucinations and ensure compliance.

• Experience: Minimum 5+ years of progressive, hands-on experience in AI/ML engineering, with a proven track record of delivering end-to-end enterprise-grade AI solutions.
• GenAI Expertise: Deep understanding of transformer architectures, prompt engineering, and the Generative AI development lifecycle.
• Framework Proficiency: Expert knowledge of Python and AI orchestration frameworks (LangChain, LlamaIndex).
• System Architecture: Experience building, deploying, and maintaining high-availability APIs and scalable systems on major cloud platforms (AWS, Azure, or GCP).
• Communication: Ability to articulate complex technical concepts and project statuses to both technical teams and executive stakeholders.
  

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Demonstrated experience in deploying AI solutions into production environments.
  

What We Offer

• Meaningful AI Work: Build practical AI solutions designed for real enterprise environments and measurable business impact.
• End-to-End Ownership: Contribute across architecture, development, deployment, evaluation, and ongoing optimisation.
• Technical Influence: Help shape engineering standards, architectural decisions, and the continued development of Quantanite’s AI capabilities.
• Modern AI Challenges: Work with multi-agent systems, advanced retrieval, LLM optimisation, and production AI engineering.
• Global Exposure: Collaborate with technical and business teams across an international organisation operating on four continents.
• Career Development: Grow your technical leadership capability while mentoring engineers and contributing to a developing AI function.
• Work Model: Hybrid role based in Mumbai, India.
• Culture: A fast-moving, collaborative, and inclusive environment where strong ideas, accountability, and practical outcomes are valued.