Job Description:
We are looking for a skilled Python Engineer with strong experience in AI/ML with exposure to Generative AI (GenAI) systems along with backend engineering expertise. The role involves building scalable APIs AI/ML and GenAI-powered services and data-driven platforms using modern cloud-native and DevOps practices.
Key Responsibilities
Design develop and maintain server-side applications using Python.
Build and expose RESTful APIs using modern frameworks.
Develop fine-tune and integrate AI/ML NLP and GenAI models into production systems.
Work with asynchronous and functional programming paradigms.
Implement data processing and feature engineering pipelines using Python libraries.
Design and interact with relational and NoSQL databases.
Build event-driven services using message queues and streaming platforms.
Containerize applications using Docker and deploy using Kubernetes/OpenShift.
Collaborate with DevOps teams to support CI/CD pipelines.
Contribute to automation and workflow platforms particularly in financial operations.
Required Skills & Qualifications
2 5 years of experience in advanced Python development.
Strong experience in server-side engineering and API development.
Hands-on experience with AI/ML NLP and Generative AI (GenAI) frameworks and libraries.
Solid understanding of AI/ML fundamentals including Deep Learning Large Language Models (LLMs) and prompt engineering.
Experience with GenAI use cases such as text generation summarization embeddings and retrieval-augmented generation (RAG).
Experience with relational (SQL) and/or NoSQL databases.
Exposure to containerization orchestration and CI/CD tools.
Preferred Qualifications
Experience with financial operations workflows or automation platforms.
Experience working in cloud-native and distributed systems.
Familiarity with deploying and scaling GenAI workloads in production environments.
Job Description: We are looking for a skilled Python Engineer with strong experience in AI/ML with exposure to Generative AI (GenAI) systems along with backend engineering expertise. The role involves building scalable APIs AI/ML and GenAI-powered services and data-driven platforms using modern clou...
Job Description:
We are looking for a skilled Python Engineer with strong experience in AI/ML with exposure to Generative AI (GenAI) systems along with backend engineering expertise. The role involves building scalable APIs AI/ML and GenAI-powered services and data-driven platforms using modern cloud-native and DevOps practices.
Key Responsibilities
Design develop and maintain server-side applications using Python.
Build and expose RESTful APIs using modern frameworks.
Develop fine-tune and integrate AI/ML NLP and GenAI models into production systems.
Work with asynchronous and functional programming paradigms.
Implement data processing and feature engineering pipelines using Python libraries.
Design and interact with relational and NoSQL databases.
Build event-driven services using message queues and streaming platforms.
Containerize applications using Docker and deploy using Kubernetes/OpenShift.
Collaborate with DevOps teams to support CI/CD pipelines.
Contribute to automation and workflow platforms particularly in financial operations.
Required Skills & Qualifications
2 5 years of experience in advanced Python development.
Strong experience in server-side engineering and API development.
Hands-on experience with AI/ML NLP and Generative AI (GenAI) frameworks and libraries.
Solid understanding of AI/ML fundamentals including Deep Learning Large Language Models (LLMs) and prompt engineering.
Experience with GenAI use cases such as text generation summarization embeddings and retrieval-augmented generation (RAG).
Experience with relational (SQL) and/or NoSQL databases.
Exposure to containerization orchestration and CI/CD tools.
Preferred Qualifications
Experience with financial operations workflows or automation platforms.
Experience working in cloud-native and distributed systems.
Familiarity with deploying and scaling GenAI workloads in production environments.
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