AI & Data Engineer
New
J
JobgetherSecurity & IT
IndiaContractSenior
Salary2,400,000 - 2,800,000 INR per year
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Job Details
- Experience
- 5+ years of relevant professional experience
- Required Skills
- PythonSQLSnowflakePandasScalaRedshiftLangChainPySpark
Requirements
- 5+ years of relevant professional experience in AI engineering, data engineering, machine learning, software engineering, or a closely related technical field.
- 2+ years of hands-on experience building and deploying AI-driven applications, with strong expertise in RAG pipelines and AI agents.
- Strong understanding of transformer architectures and practical experience working with modern LLMs such as GPT, Gemini, or Claude.
- Proven experience with advanced prompt engineering, model fine-tuning, context optimization, embeddings, and semantic search.
- Strong data engineering capabilities, including experience processing large datasets with Python, Pandas, PySpark, or Scala.
- Professional experience with Snowflake or Redshift and the ability to write advanced, performance-oriented SQL.
- Strong data modeling skills, particularly in designing dimensional models for high-quality, low-latency AI workloads.
- Experience writing clean, maintainable production code and implementing CI/CD and ML observability practices.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline is preferred.
- Experience with multi-agent systems, AWS services such as Bedrock and Lambda, or Google Gemini for multimodal and long-context applications is highly desirable.
Responsibilities
- Design, build, and deploy AI-driven applications and agentic systems capable of reasoning, information retrieval, and complex workflow execution.
- Develop and optimize Retrieval-Augmented Generation (RAG) pipelines and AI agents using frameworks such as LangChain and LlamaIndex.
- Work with large language models and transformer-based architectures, including GPT, Gemini, and Claude, applying advanced prompt engineering, fine-tuning, and context-window optimization techniques.
- Build semantic search and vector-based retrieval layers using technologies such as PGVector, embedding models, and Google indexing capabilities.
- Process and transform large-scale datasets using Python, Pandas, PySpark, or Scala to support AI and data-intensive applications.
- Design high-performance SQL solutions and scalable data warehouse architectures using platforms such as Snowflake or Redshift.
- Create dimensional data models optimized for low-latency AI consumption, scalability, and strong data quality.
- Develop clean, maintainable, production-ready software supported by robust CI/CD practices and ML observability.
- Explore advanced AI architectures, including multi-agent systems, multimodal applications, and long-context use cases.
- Contribute to the deployment and scaling of AI workloads in cloud environments, with opportunities to work across AWS and Google AI ecosystems.
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