Backend Fullstack Developer
- Getiva Solutions
2 Days Ago
55-55 per Hourly
NA
Alpharetta-GA
9-10 Years
Required Skills: Kubernetes, Databricks, Snowflake, Data modeling, API engineering, Pipeline optimization
Job Description
Job Description:
Work Mode : Hybrid - 2 days a week in the office
Work Location : "Alpharetta, GA / Plano, TX" ( Must be local from those location )
Mode of Interview : In-person
Must Have Proper Linkedin , VISA Copy , DL along with submission
Project description :
Provide software engineering in support of development to production of AI business cases. This role involves development and analytics of scalable solutions taking proof of concept to production. This position required someone who is a self-starter, self-sufficient with an open mindset and eager to learn.
Responsibilities:
Data Ingestion & Processing Architecture
Multiple high-velocity data sources, including:
Event Hub from Postgres
Data pushed to Snowflake
Additional events across various internal systems
Heavy use of
Kubernetes for scalable processing
Databricks / Spark for distributed compute
Snowflake for storage and downstream analytics
Skills :Must have
Backend Engineering:
Python (primary)
FastAPI (service/API development)
Full-stack engineering without UI (backend + data + infra only)
Cloud & Containerization:
Azure (core cloud environment)
Docker
Kubernetes / AKS
Experience running high-scale workloads in K8s
Data Engineering & Distributed Computing:
Spark / Databricks
Experience handling:
Very large datasets
Complex pipelines
High message volume
Mixed batch + streaming data flows
Designing & maintaining table schemas
Working with Snowflake
Database & Data Handling:
Strong SQL + data manipulation skills
Experience integrating multiple data sources
Comfort navigating event-streaming ecosystems
Nice to have
Hands-On LLM Integration:
Experience integrating LLMs into applications
Prompt design / optimization
RAG pipelines
Vector databases & embedding models
Model orchestration patterns
Security & compliance for AI systems
Model Monitoring & Optimization:
Prompt evaluation frameworks
Managing cost/performance tradeoffs
MLOps practices supporting AI workloads
- Kubernetes
- Databricks
- Snowflake
- Data modeling
- API engineering
- Pipeline optimization
