Senior AI Engineer M F D

Role Overview

We are seeking a highly skilled and experienced Senior AI Engineer to design, develop, and deploy advanced artificial intelligence solutions. This role involves working across the full AI lifecycle—from research and model development to production deployment and optimization—while collaborating with cross-functional teams to drive innovation and business impact.

Key Responsibilities

• Design, develop, and deploy scalable AI and machine learning models.
• Lead the development of end-to-end AI pipelines, including data preprocessing, model training, evaluation, and deployment.
• Build and optimize solutions across domains such as NLP, computer vision, recommendation systems, and generative AI.
• Collaborate with data engineers, software engineers, and product teams to integrate AI solutions into production systems.
• Optimize models for performance, scalability, and cost-efficiency.
• Research and evaluate emerging AI technologies and frameworks to drive continuous innovation.
• Establish best practices for model development, deployment, monitoring, and governance (MLOps / LLMOps).
• Mentor junior engineers and provide technical leadership within the team.
• Ensure ethical AI practices, fairness, and compliance with relevant regulations.
  
  

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (PhD is a plus).
• 7+ years of experience in AI/ML engineering or related roles.
• Strong programming skills in Python (and/or Java, C++).
• Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.
• Proven experience deploying ML models into production environments.
• Solid understanding of statistics, algorithms, and data structures.
• Experience with cloud platforms (e.g., Azure, AWS, GCP) and MLOps practices.
• Proficiency in data processing tools such as SQL, Spark, or Hadoop.
• Experience with generative AI, including large language models (LLMs) and transformer-based architectures.
  
  

• Strong analytical and problem-solving skills
• Excellent communication and collaboration abilities
• Ability to translate business requirements into scalable AI solutions
• Leadership and mentoring capabilities
  
  

• Experience developing Agentic AI workflows
• Strong understanding of the Agentic AI pipeline, including:
• Agent runtimes
• Memory management
• Agentic architectures
• LLMOps concepts
• Hands-on experience with:
• Retrieval-Augmented Generation (RAG)
• LLM fine-tuning techniques
• Experience with GenAI tools and frameworks (e.g., LangChain, Semantic Kernel, LlamaIndex, etc.)
  
  

• Experience with model serving frameworks and APIs (e.g., FastAPI, Flask).
• Knowledge of containerization and orchestration tools (Docker, Kubernetes).
• Experience with CI/CD pipelines and DevOps practices.
• Exposure to data engineering or big data ecosystems.
• Domain experience (e.g., finance, healthcare, retail, telecom) is a plus.