Lead AI Scientist / Head of AI Solutions

EstateSight AI; Abu Dhabi; On-site; AED 450,000 - 900,000; Full time

Benefits offered by this job

Opportunity to lead AI innovation with societal impact

Research-driven environment

Leadership exposure across teams

Job summary

A technology solutions firm in Abu Dhabi is seeking a visionary Lead AI Scientist / Head of AI Solutions to architect and scale cutting-edge AI systems. The ideal candidate will possess deep technical expertise in machine learning and NLP, alongside proven leadership in AI product development. Responsibilities include overseeing AI solutions across various domains, mentoring a talented team, and driving research and innovation. This role provides an opportunity to lead impactful AI innovations with potential societal benefits.

Qualifications

• Deep technical expertise in machine learning, NLP, computer vision.
• Proven leadership in AI product development.
• Experience managing AI/ML projects from concept to production.
• Develop and fine‑tune domain‑specific LLMs, ensuring alignment with enterprise data privacy and compliance standards.

Responsibilities

• Lead design, development, and deployment of AI/ML systems.
• Architect AI solutions for intelligent automation.
• Oversee cloud infrastructure and model optimization.
• Mentor and lead a high-performing team of ML engineers.
• Establish evaluation frameworks and performance metrics for AI models and deploy robust validation pipelines.
• Oversee cloud infrastructure (AWS/Azure), model optimization, and scalable API integrations using FastAPI or similar frameworks.
• Collaborate with cross‑functional teams — product, engineering, and research — to align AI solutions with business goals.
• File and manage AI‑related patents, drive intellectual property strategy, and represent the organization in research forums or industry conferences.
• Mentor and lead a high‑performing team of ML engineers, software developers, and data scientists; establish R&D processes and sprint reviews.
• Build ethical and secure AI systems with RBAC/ABAC.

Skills

Python

C/C++

SQL

NLP

Machine Learning

AI Solutions Architecture

Cloud Infrastructure

Education

Ph.D. or M.Tech in Artificial Intelligence, Computer Science, or related field

Tools

PyTorch

TensorFlow

Docker

FastAPI

Tableau

LangChain

Whisper

Hugging Face

FastAPI

Scikit-learn

Pandas

NumPy

Job description

We are seeking a visionary Lead AI Scientist / Head of AI Solutions to architect, develop, and scale cutting‑edge AI and ML systems across domains such as recruitment technology, disaster management, and enterprise automation. The ideal candidate will combine deep technical expertise in machine learning, NLP, computer vision, and large language models (LLMs) with proven leadership in AI product development, patent‑driven innovation, and research translation into scalable business solutions.

Requirements

• Lead end‑to‑end design, development, and deployment of AI/ML systems including NLP, computer vision, MLOps, and AI agent‑based architectures.
• Architect AI solutions for intelligent automation, data analytics, and human‑AI collaboration leveraging LLMs and autonomous agent frameworks.
• Drive research and innovation, translating emerging techniques into applied systems for multiple verticals (e.g., HR tech, healthcare, disaster management).
• Develop and fine‑tune domain‑specific LLMs, ensuring alignment with enterprise data privacy and compliance standards.
• Establish evaluation frameworks and performance metrics for AI models and deploy robust validation pipelines.
• Oversee cloud infrastructure (AWS/Azure), model optimization, and scalable API integrations using FastAPI or similar frameworks.
• Collaborate with cross‑functional teams — product, engineering, and research — to align AI solutions with business goals.
• File and manage AI‑related patents, drive intellectual property strategy, and represent the organization in research forums or industry conferences.
• Mentor and lead a high‑performing team of ML engineers, software developers, and data scientists; establish R&D processes and sprint reviews.
• Build ethical and secure AI systems with Role‑Based and Attribute‑Based Access Controls (RBAC/ABAC).

Required Skills & Expertise

• Programming Languages: Python, C/C++, SQL
• Frameworks & Tools: PyTorch, TensorFlow, Keras, OpenCV, Dlib, LangChain, Whisper, Hugging Face, FastAPI, Scikit‑learn, Pandas, NumPy
• NLP & LLMs: GPT models (OpenAI/Azure), RoBERTa, BERT, DistilBERT, ALBERT, prompt engineering, and fine‑tuning pipelines
• Computer Vision: Librosa, Dlib, OpenCV, multimodal signal fusion
• Cloud & DevOps: AWS (EC2, S3), Azure, Docker, Git, CI/CD pipelines
• Data Visualization: Tableau, Power BI, Matplotlib, Seaborn
• Research & Experimentation: Advanced ML model evaluation, data annotation, benchmarking, and statistical analysis
• Security & Compliance: Data governance, RBAC/ABAC, privacy‑preserving AI systems

Preferred Qualifications

• Ph.D. or M.Tech in Artificial Intelligence, Computer Science, or related field (preferably from a Tier‑1 institution such as IIT).
• Proven track record of AI patents, research publications, or applied ML innovation.
• Experience managing AI/ML projects from concept to production in fast‑paced, multi‑domain environments.
• Strong understanding of ethical AI, responsible data use, and explainability frameworks.
• Excellent communication, mentorship, and collaboration skills with both technical and non‑technical stakeholders.

Performance Metrics / KPIs

• Delivery of production‑grade AI models with measurable business impact
• Innovation output (patents, research publications, new frameworks)
• AI model accuracy, latency, and scalability benchmarks
• Team development and retention
• Contribution to enterprise AI strategy and cross‑domain integration

Benefits

• Opportunity to lead cutting‑edge AI innovation with direct business and societal impact
• Work with state‑of‑the‑art LLMs, multi‑agent systems, and autonomous AI architectures
• Research‑driven environment encouraging patents, publications, and conference participation
• Leadership exposure across R&D, engineering, and strategy teams