Principal Applied AI Architect
Information Technology
Spain
Remote
Full-time
Senior
8+ years
Posted Aug 7, 2026
About the role
A client of bytespark.ai is seeking a Principal Applied AI Architect to lead the strategy, architecture, and delivery of advanced AI solutions for high-volume voice, text, and multimodal data processing. The successful candidate will own end-to-end technical decisions for large language models, speech recognition, diffusion models, and production machine learning platforms. This role will design and fine-tune transformer-based systems for classification, entity extraction, sentiment analysis, conversational AI, and other domain-specific applications. The architect will establish scalable approaches for distributed training, model and hardware sizing, parameter-efficient fine-tuning, inference optimization, and real-time deployment. They will guide the development of robust pipelines that process billions of data points while meeting demanding reliability, security, governance, and performance expectations. The position will partner with engineering, product, research, and operational stakeholders to translate complex requirements into maintainable AI architectures and delivery roadmaps. Responsibilities include defining evaluation frameworks, monitoring model quality, directing A/B testing, and promoting reproducible, explainable, and ethical AI practices. The architect will document standards, mentor machine learning engineers, review critical designs, and advance engineering practices across multiple teams. This is an opportunity for a hands-on technical leader to shape consequential AI systems while continuously evaluating emerging research and technologies.
Requirements
- Advanced degree in Computer Science, Machine Learning, Data Science, Mathematics, or a related discipline, with at least 4 years of machine learning engineering experience focused on deep learning and neural networks.
- Principal-level experience defining end-to-end applied AI architecture, technical strategy, governance standards, design patterns, and delivery roadmaps for high-impact production programs.
- Expert Python proficiency and advanced hands-on experience with PyTorch, TensorFlow or JAX, HuggingFace Transformers, and at least one performance-oriented language such as C, C++, JavaScript, or Julia.
- Demonstrated delivery of transformer and LLM solutions using architectures such as GPT, BERT, T5, or LLaMA, including fine-tuning for NLP and conversational AI use cases.
- Production experience with ASR and speech-processing pipelines using technologies such as Whisper, Wav2Vec2, torchaudio, librosa, or SpeechBrain.
- Experience sizing, optimizing, and deploying large models using distributed training, model parallelism, quantization, pruning, distillation, ONNX, TensorRT, or comparable methods.
- Ability to build distributed multimodal pipelines and operate models with Docker, Kubernetes, MLflow, Weights & Biases, cloud ML platforms, Git, DVC, Spark, Dask, or Ray.
- Strong technical leadership, English communication, documentation, stakeholder collaboration, design review, and mentoring capabilities.
Desirable skills
- Hands-on experience with diffusion models, VAEs, GANs, synthetic data generation, and multimodal content generation.
- Knowledge of RLHF, constitutional AI, federated learning, privacy-preserving ML, explainable AI, bias detection, or adversarial machine learning.
- Experience building real-time inference and streaming architectures for telecommunications, public-sector, cybersecurity, or similarly regulated environments.
- Published AI research, patents, conference participation, or meaningful contributions to open-source machine learning projects.
- Experience with edge deployment, mobile model optimization, graph neural networks, knowledge graphs, AutoML, or neural architecture search.
Role details
- Department
- Information Technology
- Location
- Spain
- Work setup
- Remote
- Employment type
- Full-time
- Job level
- Senior
- Experience
- 8+ years
- Industry
- Technology, Information & Media
- Sub-industry
- AI Development
- Compensation
- USD 80K-90K/year + benefits structure
Frequently asked questions
This confidential recruitment process is being managed by byteSpark.ai on behalf of an established international technology organisation operating in highly specialised, mission-critical environments. byteSpark.ai is not the employer for this position. Further information about the company, engineering leadership, products, and AI roadmap will be shared with shortlisted candidates at the appropriate stage.
This is an opportunity to work on applied AI problems where reliability, performance, security, and real-world usability genuinely matter. The successful candidate will help shape AI capabilities involving Large Language Models, Agentic AI, NLP, speech, and multimodal technologies within a complex enterprise product environment. The role offers the chance to influence how AI is designed, integrated, and operationalised rather than simply consuming third-party models.
The successful candidate will design, build, fine-tune, evaluate, and deploy AI capabilities that can be integrated into real products and operational workflows. This includes developing LLM and machine-learning services, connecting models to APIs and enterprise data sources, improving inference performance, evaluating reliability, and working closely with engineering and product teams to move AI initiatives from concept into production.
The client is not building generic AI demonstrations. Its technology operates in environments where systems must be dependable, secure, explainable, and capable of handling complex data and workflows. Engineers will therefore be exposed to meaningful technical challenges involving model quality, latency, integration, deployment constraints, and production reliability.
Candidates will stand out if they can show that they have personally taken AI systems beyond experimentation. Strong evidence of production LLM applications, model fine-tuning, Agentic AI workflows, enterprise integration, PyTorch, Hugging Face, MLOps, optimisation, and measurable technical or commercial outcomes will significantly strengthen an application.
The client is looking for a hands-on engineer who can move confidently between model development, software engineering, experimentation, and production delivery. The ideal candidate is intellectually curious, technically rigorous, comfortable taking ownership, and motivated by solving difficult applied AI problems rather than working only on research or isolated prototypes.
The role is expected to offer meaningful technical ownership. The successful candidate will contribute to architecture decisions, model selection, experimentation, deployment approaches, and the development of reusable AI capabilities. This is not a narrow implementation role; the engineer will help shape how the organisation applies AI across its product environment.
The position is based in Portugal. Compensation will be aligned with the candidate's experience, technical depth, and overall fit for the role. Further details regarding salary, benefits, working arrangements, and any applicable relocation support will be discussed with shortlisted candidates during the recruitment process.