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

Awisee 2022; Polska; Hybrid; PLN 180,000 - 240,000; Full time

Job summary

AWISEE is seeking a Lead AI Systems Architect to design and scale automated classification, enrichment, and multimodal AI pipelines. You will transform raw, unstructured social content into high-precision structured data products.

You will lead data-centric AI initiatives, guide junior engineers, implement validation frameworks, optimize models from commercial APIs to open-source solutions, and shape the data enrichment architecture for scalable social media intelligence.

Qualifications

• 5+ years of experience in Applied AI, Natural Language Processing, or Computer Vision.

Responsibilities

• Design multimodal AI pipelines integrating vision, speech, and text models.

Skills

Python

PyTorch

TensorFlow

LLM orchestration

Data pipelines

Leadership

Tools

DSPy

Instructor

Pydantic

LangChain

LlamaIndex

vLLM

TGI

Groq

Qdrant

pgvector

Pinecone

Job description

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

Founded in 2018, AWISEE is a global digital marketing agency specializing in SEO, Digital PR, and KOL & Influencer Marketing. We help brands enter new markets or expand within existing ones, combining short-term visibility strategies and long-term growth solutions to drive impactful, measurable results.

Global Reach & Industry Expertise Operating across Europe, North America, Asia, and the Middle East, AWISEE tailors strategies to each market for cultural fit and compliance. We specialize in Tech & SaaS, Fintech, E-commerce, Crypto, iGaming, Travel - driving impactful growth worldwide.

Job Description

This is a remote position.

We are building a an AI & Data Lab focused on social media intelligence and influencer marketing data. We are seeking a Lead AI Systems Architect to design and scale our automated classification, enrichment, and multimodal AI pipelines. You will take raw, unstructured social content (short-form video, audio, captions, and visual metadata) and convert it into high-precision structured data products.

Responsibilities

• Design & Build Multimodal AI Pipelines: Combine Computer Vision (scene classification, aesthetic scoring), Speech-to-Text (Whisper), and LLMs into automated ingestion workflows.
  
• Structured Data Extraction: Implement programmatic extraction frameworks (Instructor, Pydantic, DSPy, Outlines) to enforce strict, validated JSON outputs from generative models.
  
• Model Optimization & Cost Control: Transition workloads from commercial APIs to fine-tuned open-source models (Llama 3/4, Qwen, DeepSeek) running on local inference engines (vLLM, TGI, Groq).
  
• Programmatic Labeling & Quality Control: Deploy data-centric AI frameworks (Cleanlab, Snorkel, Active Learning) to automate millions of labels and clean noisy datasets.
  
• Technical Leadership: Guide junior developers, establish engineering best practices, and set architectural roadmaps for data enrichment.
  

Requirements

• 5+ years of experience in Applied AI, Natural Language Processing, or Computer Vision.
  
• Proven experience building multimodal pipelines integrating vision, speech, and text models.
  
• Mastery of Python, PyTorch/TensorFlow, and production LLM orchestration tools (DSPy, Instructor, Pydantic, LangChain/LlamaIndex).
  
• Hands-on experience fine-tuning and serving open-source models using vLLM, TGI, or similar high-throughput inference engines.
  
• Experience with vector databases (Qdrant, pgvector, Pinecone) and RAG architectures at scale.
  

Preferred Qualifications

• Prior experience with social media data pipelines (TikTok, Instagram Reels, YouTube Shorts).
  
• Background in data-centric AI, active learning, or synthetic data generation.