Senior AI Engineer, Translations & Language Solutions

Senior AI Engineer – LLM & Agentic Systems (Translations & Language Technology)

Location: UK, Spain, Poland, Portugal, Czech Republic, home based

Role Summary

IQVIA Language Solutions is seeking a hands-on AI Engineer with expertise in Large Language Models (LLMs) and Agentic AI to design, build, and scale next-generation language technology solutions. This role sits at the intersection of AI engineering, localization technology, and service delivery, and will directly impact how multilingual content is produced, reviewed, evaluated and delivered at scale.

The successful candidate will combine strong engineering capability with applied AI experience, and work closely with technology team, product owners, linguists and stakeholders to deliver production-grade AI systems in a regulated environment.

Responsibilities

• Design and implement LLM-powered solutions for translation, localization, linguistic QA, content transformation and workflow automation.
• Build and maintain agentic AI systems to orchestrate translation, review, quality checks and analysis tasks.
• Develop frameworks to enhance LLM output through contextual targeting (e.g. through retrieval-augmented generation or contextual engineering/agentic pipelines using translation memories, term bases, style guides and data content factories).
• Integrate LLM solutions into existing translation management systems, CAT tools and enterprise systems via APIs and services.
• Innovate: Experiment, Prototype and Build targeted AI solutions. Stay current with advances in LLMs, agent and evaluation frameworks, as well as deployment methods
• Implement prompt engineering, prompt versioning, evaluation, and optimization strategies tailored to multilingual and domain-specific use cases. Validate prompt outputs through both qualitative and quantitative evaluation procedures.
• Establish robust LLM evaluation frameworks to evaluate performance of AI output covering quality, consistency, risk, bias and regulatory adherence
• Analyse and derive insights from large amounts of data to support solution decisions
• Develop and maintain datasets for LLM output validation, including designing annotation guidelines, performing quality control, creating tools for data analysis or data creation (synthetic or sourced data)
• Create technical architecture, design and deployment documents for the solutions   
• Contribute to AI governance, documentation, and best-practice standards

Skills

Core Technology Skills

• Strong proficiency in Python (required); experience with modern ML/AI frameworks.
• Hands-on experience with LLMs (e.g. Azure OpenAI GPT, Claude, LLaMA).
• Ability to build agentic systems using frameworks such as LangChain, LangGraph or equivalent (tracing, evaluation, monitoring).
• Expertise in RAG architectures, vector databases (e.g., FAISS, Azure AI Search) and embedding strategies.
• Solid understanding of NLP and machine translation concepts, including domain adaptation and multilingual challenges.
• Knowledge of API design, microservices, and cloud-native architectures (Azure, AWS).
• Proficient in creation and management of datasets, annotation workflows, and quality control in the AI context
• Strong understanding of prompt engineering principles and experience with prompting LLMs.
• Familiarity with data pipelines, document processing (PDF, XML, HTML), and content transformation workflows.

Domain and Soft Skills

• Solid understanding of localization technology and operations including CAT tools, TMS, Linguistic assets and quality metrics.
• Knowledge of AI safety, bias detection and human-in-the-loop design.
• Problem-solving skills, balancing tech innovation with operational reliability and practicality
• Ability to translate technical concepts into clear guidance for users and stakeholders.
• Collaboration and influencing skills across teams (engineering, product, operations)
• Pragmatic and outcome-driven with a focus on operational results
• Comfortable working in a fast-evolving AI landscape with ambiguity and experimentation

Experience

• Formal qualification in a technology discipline or equivalent experience
• 5+ years of professional experience in ML or applied AI roles
• 1+ years of hands-on experience working with LLMs in language solutions environment
• Demonstrable experience in designing and deploying LLM/Agent based multi-step AI workflows.
• Experience working with AI-embedded development tools (e.g. Cursor)
• Proven track record of delivering AI solutions creation and integration with existing systems, preferably with a Language Service Provider or localization technology company
• Experience in healthcare or life sciences domain is an advantage
• Research experience in Computational Linguistics (or equivalent) field is an advantage

As an essential and recurring component throughout a healthcare product’s development and commercialization, Language Solutions have a high impact on critical areas in life sciences. IQVIA Language Solutions provide a wide range of language services to the industry, backed by our technology solutions. We address unmet needs by embedding latest technology innovations within our solutions, in order to provide language solutions of high quality and efficiency.

This role is not eligible for UK visa sponsorship.

IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com

IQVIA is committed to integrity in our hiring process and maintains a zero tolerance policy for candidate fraud. All information and credentials submitted in your application must be truthful and complete. Any false statements, misrepresentations, or material omissions during the recruitment process will result in immediate disqualification of your application, or termination of employment if discovered later, in accordance with applicable law. We appreciate your honesty and professionalism.