AI Engineer

Senior AI Engineer

As a Senior AI Engineer, you'll be at the forefront of applying cutting-edge AI technologies to solve real-world challenges. You'll work with a team dedicated to building AI-powered solutions that help global enterprises understand, manage, and automate complex processes across multiple markets and jurisdictions.

Core Responsibilities:

Product Development & Innovation:

• Identify and implement opportunities where AI can create tangible value for customers.
• Design and develop production-grade AI solutions that automate complex tasks.
• Build and optimize advanced NLP models for document analysis and interpretation.
• Contribute to finding the right ML framing of industry challenges.
• Create scalable AI systems that can handle diverse requirements across different markets.

Technical Leadership:

• Take algorithms from proof-of-concept to production, ensuring robustness and scalability.
• Establish processes for large-scale data analysis, model development, validation, and deployment.
• Build and maintain ML infrastructure that can evolve with growing needs.
• Implement monitoring systems to track model performance and accuracy.
• Ensure AI solutions maintain high standards of explainability and ethical considerations.

Cross-functional Collaboration:

• Work closely with product managers and subject matter experts to translate business requirements into technical solutions.
• Partner with engineering teams to integrate AI capabilities into the core platform.
• Contribute to technical documentation and knowledge sharing.
• Participate in architecture discussions and technical decision-making.

Key Skills:

• 5+ years of hands-on experience in production environments, with a strong track record of designing and architecting distributed systems.
• Experience developing and deploying production-grade software using ML frameworks such as TensorFlow, PyTorch, etc.
• Deep understanding of engineering and infrastructure best practices, with a focus on the ML software development lifecycle.
• Expertise in building, fine-tuning, and optimizing Large Language Models (LLMs), transformer architectures, and advanced NLP systems using frameworks like Hugging Face and OpenAI SDKs.
• Strong background in modern deep learning techniques, LLMs, and data-intensive applications.
• Familiarity with state-of-the-art agentic AI frameworks (e.g., LangChain, AutoGen, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, Google's ADK) and experience orchestrating multi-agent workflows.
• Knowledge of techniques for optimizing ML inference performance.
• Hands-on expertise designing and managing batch and real-time ML pipelines/workflows for structured and unstructured data on AWS (SageMaker, ECS, EKS, Airflow).
• Familiarity with LLMOps and observability tools (Langsmith, Opik, Ragas, Weights & Biases) for monitoring, evaluation, and governance.
• Excellent communication skills and the ability to collaborate effectively across teams.