AI Engineer

RudraX Global is building the technology consulting firm of the future — combining the strategic rigour of a top-tier management consultancy with the engineering depth of a world-class software house. We work with ambitious clients across FinTech, HealthTech, and enterprise technology, delivering AI-driven solutions that create measurable, lasting impact.

We are looking for an AI Engineer who doesn't just write models — but thinks like a product builder and communicates like a consultant. You will work directly on high-stakes client engagements, shaping intelligent systems from first principles through to production deployment.

If you want to do meaningful AI work — not just integrations and wrappers — and grow inside a firm with genuine top-tier consulting ambitions, this role is for you.

• Architect, train, fine-tune, and deploy small language models (SLMs) tailored to specific client domains and use cases
• Work extensively with open-source language models — evaluating, adapting, and optimising them for real-world production environments
• Build robust AI pipelines including retrieval-augmented generation (RAG) systems, agentic workflows, and tool-calling architectures
• Translate complex client requirements into clear technical specifications and scalable AI solutions — bridging the gap between business need and engineering output
• Contribute to product thinking: participate in scoping sessions, challenge assumptions, and help shape the AI features that matter most to end users
• Communicate findings, model behaviour, trade-offs, and recommendations clearly to both technical and non-technical stakeholders — including senior client contacts
• Collaborate cross-functionally with product managers, backend engineers, and frontend developers across the UK and India
• Maintain rigorous standards for model evaluation, testing, monitoring, and documentation in production
• Stay at the frontier — actively tracking open-source AI developments and assessing their applicability to client engagements

• 2+ years of hands-on experience in AI/ML engineering or applied research
• Demonstrable experience building or fine-tuning small language models (SLMs) — not just consuming third-party APIs
• Deep familiarity with the open-source model ecosystem and the ability to evaluate, adapt, and deploy models critically for client-specific requirements
• Strong Python skills and proficiency with core AI/ML libraries and frameworks
• Solid understanding of product development lifecycles — you think about the user, the use case, and the business outcome, not just the model
• Excellent communication skills — written and verbal — with the ability to present technical concepts clearly and confidently to non-technical audiences
• Experience integrating AI capabilities into production systems via REST APIs or microservices
• Familiarity with vector databases and semantic search technologies
• Ability to work independently, manage your own delivery, and thrive in a consulting-style, client-facing environment

• Experience with quantisation, distillation, or reinforcement learning from human feedback (RLHF) techniques for model optimisation
• Exposure to MLOps tooling — experiment tracking, model registries, and continuous integration/deployment pipelines for machine learning systems
• Cloud platform deployment experience
• Prior experience in a consulting, agency, or client-services environment
• Familiarity with modern frontend frameworks for building AI-powered product interfaces
• Understanding of data privacy, compliance, and on-premise deployment constraints relevant to enterprise clients