AI Engineer

Overview

is a fast-growing AI-first technology services company, partnering with enterprises to shape and accelerate their journey to AI maturity. With a presence across the US, UK, UAE, India, and Singapore, we bring together deep domain knowledge, cloud-scale engineering, and cutting-edge artificial intelligence to help our clients transform into agile, insight-driven organizations.

We are proud partners with global technology leaders such as Databricks, Microsoft, AWS, and Qlik, and have been consistently recognized for innovation, delivery excellence, and trusted advisories.

Awards & Recognitions

• Innovation Partner of the Year – Databricks, 2024
• Digital Impact Award, UK – 2024 (TMT Sector)
• Rising Star – APJ Databricks Partner Awards 2023
• Qlik’s Most Enabled Partner – APAC
  
  

With a team of 450+ AI engineers, data scientists, and consultants, we are on a mission to redefine how work is done, by combining human intelligence with AI agents to deliver exponential outcomes.

Learn more: www.exponentia.ai

About the Role: AI Engineer

We are seeking a highly skilled AI Engineer with 5+ years of hands-on experience in AI/ML, Generative AI, and Agentic AI systems. The ideal candidate will have a deep understanding of AI agent frameworks, Model Context Protocol (MCP), Databricks, and cloud-native MLOps workflows. This role involves building, deploying, and optimizing intelligent systems — from LLM-powered applications to autonomous multi-agent architectures.

Key Responsibilities

• Design, develop, and deploy machine learning and generative AI models in production environments.
• Build and integrate agentic AI systems — intelligent agents capable of reasoning, planning, and multi-step decision-making.
• Develop and maintain data pipelines and MLOps workflows using Databricks, MLflow, and cloud-native tools.
• Integrate LLMs and AI agents with external APIs, databases, and tools using agent frameworks (LangChain, AutoGen, CrewAI, Semantic Kernel, LangGraph).
• Implement and manage Model Context Protocol (MCP) connections between agents and enterprise systems.
• Optimize AI workloads in AWS, Azure, or GCP environments with scalable, secure infrastructure.
• Collaborate with cross-functional teams (data, cloud, and product) to deliver AI-driven solutions.
• Ensure AI system security, observability, explainability, and compliance with governance standards.