Our client is a financial services group with an integrated global network. Our client builds and maintains software solutions used by agency-model execution business. The business provides brokerage services to clients in over 65 markets around the world. Through its advanced suite of electronic trading strategies, experienced high-touch trading group, top-ranked Commission Management services, award-winning desktop trading platform, and unparalleled access to insightful analytics, content and unique liquidity, execution services business helps institutions lower overall trading costs and ultimately improve investment performance.

Position Type: Permanent
Experience: 8 - 13yrs
Hands-on experience in AI Engineering, AI Developer, AI agents, AI solutions, Python, Javascript, NodeJs, Typescript, cloud platform, Docker, Kubernetes, Generative AI, LLM, Agentic AI, AI Agents, MLOps.

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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.
Stay ahead of the latest advancements in AI, machine learning, and software engineering, and apply this knowledge to your work.
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 robust 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., Knowledge of data engineering principles and experience with data storage and processing technologies like BigQuery.
An understanding of the ethical considerations and potential biases in AI and predictive algorithms.

📌 AI Engineer (Permanent) (Secunderabad)
🏢 The Edge Partnership
📍 Secunderabad