Lead AI Systems Architect (Data-Centric AI & Multimodal)

Jobgether SRL; Schweiz; Remote; CHF 10,000 - 13,000; Full time

Benefits offered by this job

Fully remote

Competitive salary

Leadership role

Open-source deployment

Job summary

Jobgether is seeking a Lead AI Systems Architect (Data-Centric AI & Multimodal) based in Switzerland. The role focuses on designing expert AI systems that transform unstructured social media content into structured data products, building multimodal pipelines, and guiding junior developers within a growing AI/Data Lab.

You will drive open-source model adoption, optimize inference infrastructure, and help shape the technical architecture of the lab, while mentoring teammates and establishing

Qualifications

• At least 5 years of experience in applied AI, NLP or computer vision.
• Proven experience designing multimodal pipelines that integrate vision, speech, and text models.
• Advanced proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Strong experience with production LLM orchestration and structured output tools (DSPy, Instructor, Pydantic, LangChain, LlamaIndex).
• Hands-on experience fine-tuning and serving open-source models using vLLM, TGI, or comparable engines.
• Experience with vector databases and retrieval-augmented generation at scale.
• Ability to establish technical best practices, make architectural decisions, and mentor junior developers.

Responsibilities

• Multimodal AI Pipeline Development: design and build automated ingestion pipelines integrating vision, speech, and text models.
• Structured Data Extraction: develop programmatic extraction frameworks to produce consistent JSON outputs.
• Model Optimization and Cost Management: migrate workloads to open-source models and efficient inference engines.
• Data Labeling and Quality Assurance: implement data-centric AI techniques to automate large-scale labeling and improve data quality.
• AI Architecture and Technical Leadership: define roadmaps, establish engineering standards, mentor juniors.
• Scalable Data Infrastructure: support AI-driven enrichment workflows and retrieval systems for unstructured content.

Skills

Python

NLP

Computer Vision

Model optimization

Leadership

Tools

Instructor

Pydantic

DSPy

LangChain

LlamaIndex

vLLM

TGI

Groq

Job description

Lead AI Systems Architect (Data-Centric AI & Multimodal) based in Switzerland

This is an opportunity for an experienced AI engineer to design and scale advanced AI systems that transform unstructured social media content into high-quality, structured data products.

You will lead the development of multimodal pipelines combining computer vision, speech recognition, and large language models. The role focuses on building reliable data extraction workflows, optimizing model performance, and improving the quality of large-scale datasets.

You will also drive the adoption of open-source models and efficient inference infrastructure to improve scalability and control costs. Working at the intersection of applied AI, data engineering, and social media intelligence, you will help shape the technical architecture of an evolving AI and Data Lab.

You will also provide technical guidance to junior developers and establish engineering practices that support sustainable growth.

Accountabilities

• Multimodal AI Pipeline Development: Design and build automated ingestion pipelines combining computer vision for scene classification and aesthetic scoring, speech-to-text technologies such as Whisper, and large language models.
• Structured Data Extraction: Develop programmatic extraction frameworks using tools such as Instructor, Pydantic, DSPy, and Outlines to ensure generative models produce consistent, validated JSON outputs.
• Model Optimization and Cost Management: Transition workloads from commercial AI APIs to fine-tuned open-source models, including Llama, Qwen, and DeepSeek, deployed through local or high-throughput inference engines such as vLLM, TGI, and Groq.
• Data Labeling and Quality Assurance: Implement data-centric AI techniques and frameworks, including Cleanlab, Snorkel, and active learning, to automate large-scale labeling processes and improve the quality of noisy datasets.
• AI Architecture and Technical Leadership: Define architectural roadmaps, establish engineering standards, and guide junior developers in building robust, maintainable AI systems.
• Scalable Data Infrastructure: Support the development of AI-driven enrichment workflows and retrieval systems capable of processing large volumes of unstructured content efficiently.

Requirements

• At least 5 years of experience in applied AI, natural language processing, or computer vision.
• Proven experience designing and implementing multimodal pipelines that integrate vision, speech, and text models.
• Advanced proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Strong experience with production LLM orchestration and structured output tools, including DSPy, Instructor, Pydantic, LangChain, or LlamaIndex.
• Hands-on experience fine-tuning and serving open-source models using vLLM, TGI, or comparable high-throughput inference engines.
• Experience with vector databases such as Qdrant, pgvector, or Pinecone, and with retrieval-augmented generation (RAG) architectures at scale.
• Ability to establish technical best practices, make architectural decisions, and mentor junior developers.

Preferred Qualifications

• Experience building social media data pipelines involving platforms such as TikTok, Instagram Reels, or YouTube Shorts.
• Background in data-centric AI, active learning, or synthetic data generation.

Benefits

• Fully remote working arrangement.
• Annual salary of $12,000–$16,000.
• Opportunity to work on advanced multimodal AI systems, open-source model deployment, and large-scale data intelligence.
• Technical leadership opportunities, including architectural planning and mentoring junior developers.

How Jobgether Works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.