AI Engineer

Role Summary

We are looking for an experienced and hands-on AI Data Engineer to design develop and operationalize secure scalable production-grade Generative AI agentic AI and cloud data solutions.

The successful candidate will combine strong AI engineering capabilitiesincluding large language models prompt engineering retrieval-augmented generation vector search AI agents and LLMOpswith a solid foundation in Python advanced SQL databases and cloud-based data engineering.

The candidate should be also be able to work in establishing data pipelines and engineeringfrom data ingestion and preparation to data modeling deployment and monitoring.

AI & Data Engineer

Design build and operate secure scalable production-grade Generative AI agentic AI and cloud data solutions for analytics and reporting.

Develop LLM applications for analytics and reporting using prompt engineering retrieval-augmented generation (RAG) embeddings vector search structured outputs tool calling function calling fine-tuning and model routing.

Build AI agents that retrieve enterprise data use approved tools and APIs coordinate multi-step workflows and operate within defined guardrails and human oversight.

Integrate foundation models AI agents enterprise data platforms APIs workflow orchestration tools document repositories and reporting applications.

Develop AI capabilities such as natural-language querying conversational analytics automated summaries intelligent recommendations anomaly detection narrative reporting and workflow automation.

Design develop and maintain robust ETL/ELT pipelines for structured and unstructured data across data lakes warehouses and lake houses.

Design serverless event-driven and cost-efficient cloud architectures using a primary cloud platform such as AWS Azure or GCP.

Develop data models data-quality frameworks validation rules metadata lineage and reusable data products.

Build production-grade services using Python SQL APIs CI/CD automated testing infrastructure as code and observability practices.

Apply responsible AI practices including data privacy security access control content safety prompt-injection protection and prevention of sensitive-data leakage.

Deploy AI solutions using services such as Amazon Bedrock Amazon SageMaker Azure OpenAI Azure AI Foundry Google Vertex AI OpenAI APIs vector databases and enterprise search platforms.

Develop and orchestrate data workflows using AWS Glue Glue Workflows AWS Lambda Step Functions Amazon S3 Athena Redshift and Amazon RDS.

Partner with data technology and business stakeholders to translate requirements into data models AI features visualizations and actionable insights.

Mandatory Technical Skills

AI and Generative AI

Strong understanding of Generative AI and large language model concepts.

Hands-on experience developing LLM-based applications.

Practical experience with:

o Prompt engineering and prompt templates

o Retrieval-augmented generation

o Embeddings and semantic search

o Vector search and vector databases

o Document ingestion and chunking

o Structured LLM outputs

o Context and conversation management

o AI-agent development

o Multi-step agentic workflows

o Model evaluation and response validation

Programming

Strong hands-on programming experience in Python.

Good understanding of object-oriented programming data structures exception handling logging API integration and asynchronous processing.

Experience with relevant Python libraries and frameworks such as:

o Pandas

o PySpark

o Boto3

o FastAPI or Flask

o LangChain

o LangGraph

o LlamaIndex

SQL Databases and Data Engineering

Strong proficiency in writing and optimizing advanced SQL queries.

Hands-on experience with complex joins and subqueries Window and analytical functions and stored procedures

Preferred Technical Skills

Exposure to business intelligence and reporting tools particularly Microsoft Power BI or Tableau