AI Engineer at Citi

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

18 Mar, 26

Salary

0.0

Posted On

18 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Generative AI, MLOps, Full-Stack Development, Prompt Engineering, Semantic Search, RAG Solutions, Agent-Based Solutions, Python, Flask, FastAPI, LangChain, Hugging Face, PyTorch, TensorFlow, AWS, Azure, GCP

Industry

Financial Services

Description

Develop and deploy production-grade Generative AI applications, with a strong focus on building highly effective prompts, semantic search solutions, and robust RAG/Agentic pipelines. Engage in full-stack development, contributing to both the front-end and back-end of AI-powered applications. Implement and maintain MLOps pipelines for continuous integration, delivery, and monitoring of AI models. Contribute to the end-to-end ML model development lifecycle, including data understanding, feature engineering, algorithm selection, and validation. Collaborate with cross-functional teams to translate business requirements into technical solutions. Write clean, scalable, and well-documented code, adhering to software development best practices. Assist in evaluating and integrating new AI technologies and frameworks to enhance existing solutions. 2-4 years of overall experience with a minimum of 1.5 years of experience in developing production-grade Gen AI based RAG solutions or Agent-based solutions. Proven experience as a full-stack developer, with hands-on experience in building and deploying production-ready applications. Strong understanding of the Gen AI development process, including prompt engineering, semantic search, and RAG/Agentic pipeline development. Proficiency in Python and experience with relevant frameworks (e.g., Flask, FastAPI, LangChain, Hugging Face). Experience with deep learning frameworks such as PyTorch or TensorFlow. Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes). Familiarity with MLOps principles and tools (e.g., MLflow, Kubeflow, Sagemaker). Strong problem-solving skills and the ability to work independently on assigned tasks. Bachelor's/University degree or equivalent experience in Computer Science, Engineering, or a related quantitative field. ------------------------------------------------------ For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------

Responsibilities

Develop and deploy production-grade Generative AI applications, focusing on effective prompts and robust pipelines. Collaborate with cross-functional teams to translate business requirements into technical solutions.