Python/PySpark Developer
HAN IT STAFFING, INC.
Hanover, NJ, United States
5 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source
Tech stack
Java (Programming Language)
Application Programming Interfaces (APIs)
Amazon Web Services
Amazon Elastic Compute Cloud
Amazon S3
Application Integration Architecture
Cloud Engineering
Databases
Continuous Integration
Identity and Access Management
Python (Programming Language)
Enterprise Messaging Systems
+24 more
Cloud Services
Search Technologies
Software Engineering
SQL Databases
Retrieval-Augmented Generation
Flask (Web Framework)
Large Language Models
Prompt Engineering
Spring-boot
Generative AI
Amazon Virtual Private Cloud (VPC)
Fastapi
Data Lakes
Pyspark
Kubernetes
Machine Learning Operations
Functional Programming
Api Design
Cloudwatch
Restful APIs
Model Inference
Docker
Databricks
Microservices
Requirements
- Hands-on experience developing production-grade solutions using Python and PySpark., * Strong application engineering experience with the ability to design, develop, test, and deploy production-grade applications.
- Hands-on experience building REST APIs and microservices using languages/frameworks such as Python (FastAPI/Flask) or Java (Spring Boot).
- Good understanding of end-to-end application development, including API design, service integration, authentication/authorization, configuration, testing, CI/CD, observability, scalability, and production support.
- Experience integrating applications with cloud services, databases, messaging platforms, and external/internal APIs.
AWS & Cloud Architecture:
- Strong understanding of AWS cloud architecture and cloud-native data/application solutions.
- Hands-on experience with Amazon S3, IAM, EC2, Lambda, EKS, RDS, CloudWatch, Secrets Manager, KMS, and VPC/networking.
- Strong understanding of IAM roles/policies, encryption, private connectivity, security groups, and cross-account access.
- Experience designing secure, scalable, and highly available applications on AWS.
Generative AI/LLM Engineering:
- Experience deploying and operationalizing Large Language Models (LLMs) in production.
- Hands-on experience with LLM inference, model serving, prompt engineering, embeddings, RAG, and vector search.
- Experience integrating LLM capabilities into production applications and APIs.
Nice to Have:
- Hands-on experience with Delta Lake, Unity Catalog, Databricks Workflows/Jobs, MLflow, notebooks, clusters/compute, and SQL Warehouses.
Experience with containerized application deployment using Docker/Kubernetes/EKS and automated CI/CD pipelines.
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Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
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