Sr. Software Engineer Python (Remote)

Company Overview

Vilasitawear is a forward-thinking company committed to innovation and excellence. Our mission is to deliver high-quality software solutions that empower businesses to achieve their goals. We value collaboration, creativity, and continuous learning, fostering a work culture where every team member can thrive. With a focus on technological advancement, we are looking for talented individuals to join our dynamic team.

Role Responsibilities

• Lead backend development to support AI and ML model deployment, orchestration, and integration
• Design and scale microservices and RESTful APIs for AI platforms Partner with data scientists and ML engineers to ensure seamless data and model integration
• Own system scalability, performance, and reliability
• Build and manage CI/CD pipelines ensuring secure, high-quality code delivery
• Participate in rotating on-call support (1 week every 6 weeks)
• Mentor junior engineers and lead technical reviews

Skills

• Vector Databases (Qdrant, AWS OpenSearch)
• Event-driven Architecture (Kafka, SQS, SNS, Kinesis)
• Monitoring Tools (Grafana, Prometheus, ELK, Datadog)
• LLM Hosting Platforms (e.g., AWS Bedrock)
• Java Microservices (Spring Boot)
• Java Async Frameworks (Project Reactor, RxJava)
• Distributed Computing (Spark, Flink, Snowflake, Ray)
• Infrastructure As Code (CDK, Terraform)
• SQL And NoSQL Databases (PostgreSQL, Cassandra, DynamoDB)
• LLM / GenAI Exposure (LangChain, LLM APIs)
• API Design (scalable, Versioned APIs)
• CI/CD Pipelines
• Python (including Design Patterns & Libraries)
• Async Programming In Python
• Microservices (FastAPI, Flask, Django)
• Docker
• Kubernetes / AWS ECS
• AWS, Azure, Or GCP (Cloud Platforms)

Skills: cloud technologies,python (including design patterns & libraries),monitoring tools (grafana, prometheus, elk, datadog),agile methodologies,unit testing,database management,collaboration tools,llm / genai exposure (langchain, llm apis),ci/cd pipelines,infrastructure as code (cdk, terraform),aws, azure, or gcp (cloud platforms),microservices (fastapi, flask, django),async programming in python,restful apis,llm hosting platforms (e.g., aws bedrock),java async frameworks (project reactor, rxjava),distributed computing (spark, flink, snowflake, ray),vector databases (qdrant, aws opensearch),problem solving,java microservices (spring boot),event-driven architecture (kafka, sqs, sns, kinesis),sql and nosql databases (postgresql, cassandra, dynamodb),api design (scalable, versioned apis),kubernetes / aws ecs,docker