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We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long-term project. Here are a few details.
Experience:6-8 Years
Requirements
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
capabilities—including large language models, prompt engineering,
retrieval-augmented generation, vector search, AI agents, and LLMOps—with 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
engineering—from 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
Benefits
Skills Required
- 6–8 years of professional experience
- Strong understanding of Generative AI and large language model concepts
- Hands-on experience developing LLM-based applications
- Experience with prompt engineering, RAG, embeddings, semantic search, vector databases, document ingestion, structured outputs, conversation management, AI agents, agentic workflows, model evaluation, and response validation
- Strong hands-on programming experience in Python
- Understanding of object-oriented programming, data structures, exception handling, logging, API integration, and asynchronous processing
- Experience with Pandas, PySpark, Boto3, FastAPI or Flask, LangChain, LangGraph, and LlamaIndex
- Strong proficiency writing and optimizing advanced SQL queries
- Experience with complex joins, subqueries, window and analytical functions, and stored procedures
- Experience designing ETL/ELT pipelines, data models, data-quality frameworks, metadata, lineage, and data products
- Experience with cloud architecture and data engineering on AWS, Azure, or GCP
- Exposure to Microsoft Power BI or Tableau
What We Do
Alignity is a Talent Solutions company focused on revolutionizing talent acquisition, employer branding, and performance inspiration to help organizations achieve accelerated growth.
