About the Role :

Our client is a financial services group with an integrated global network. They build and maintain software solutions used by agency-model execution businesses. The business provides brokerage services to clients in over 65 markets around the world.

Key Responsibilities :

- Design, build, test, and deploy scalable and reliable AI-powered applications, with a primary focus on AI Agents.

- Collaborate closely with data scientists, product owners, and other engineers to translate concepts into production-grade software.

- Develop and maintain the full lifecycle of AI solutions, from data ingestion and processing to model deployment and monitoring.

- Implement and manage MLOps pipelines to ensure efficient and automated training, evaluation, and deployment of predictive algorithms.

- Write high-quality, maintainable, and well-tested code in languages such as Python, Java, or Node.js.

- Ensure the security, scalability, and observability of the AI systems you build within our cloud-native environment.

- Participate in code reviews, providing and receiving constructive feedback to maintain high engineering standards.

- Stay ahead of the latest advancements in AI, machine learning, and software engineering, and apply this knowledge to your work.

Requirements :

- Proven experience in a software engineering role with a focus on building and deploying applications.

- Strong proficiency in at least one of the following programming languages : Python or the JavaScript runtime Node.js with Typescript.

- Proven understanding of software development principles, including experience in building scalable and observable solutions.

- Hands-on experience with at least one major cloud platform (GCP, Azure, or AWS) and a strong grasp of cloud-native architectures.

- Experience with containerization technologies such as Docker and orchestration platforms like Kubernetes.

- A foundational understanding of concepts in artificial intelligence, including supervised and unsupervised learning, and the lifecycle of a machine learning project.

- Familiarity with emerging trends and technologies in AI, such as Generative AI, Large Language Models (LLMs), and Agentic AI architectures.

- Experience with Agile development methodologies and tools like Jira.

- Practical experience developing applications that demonstrate advanced conversational AI models and frameworks for crafting AI Agents (e.g. Google ADK, LangChain, CrewAI).

- Experience with MLOps tools and frameworks such as MLflow or Kubeflow.

- Familiarity with data processing alongside artificial intelligence frameworks in Python (e.g., pandas, scikit-learn, TensorFlow, or PyTorch).

- Knowledge of data engineering principles and experience with data storage and processing technologies like BigQuery.

Mandate :

- Only candidates who are available for a Face-to-Face interview on 31st Oct'26, should apply.

- LOOKING ONLY FOR IMMEDIATE CANDIDATES/SERVING NOTICE PERIOD.