Noblesoft Solutions
Senior Python Application Developer (RAG AI)
Noblesoft Solutions, St. Petersburg, Florida, United States, 33739
Senior Information Technology Recruiter at Noblesoft Solutions
Contract Duration: 10+ Months
Hybrid role based in St. Petersburg, FL
Technical Responsibilities
Architect, design, and optimize
Python-based RAG (Retrieval-Augmented Generation)
systems for real-world deployment.
Build and maintain
vector databases
and
embedding pipelines
using
Redis ,
Faiss , or similar high-performance stores.
Develop and manage
GPU-accelerated pipelines
for embedding generation and model vectorization.
Design and operate
Kubernetes (K8s)
environments for scaling distributed microservices and model workloads.
Integrate retrieval and generation components into larger
AI/LLM ecosystems
with high throughput and reliability.
Own performance tuning, profiling, and system observability for millisecond-level responsiveness.
Contribute to automation, CI/CD pipelines, and infrastructure-as-code practices.
Collaborate closely with AI engineers, data scientists, and DevOps to deliver production-grade, fault-tolerant systems.
Core Technical Qualifications
5+ years
of experience in
Python
software engineering for production systems.
Deep expertise with
Redis ,
Kubernetes , and
GPU-based computation
(CUDA, PyTorch, or TensorFlow).
Proven experience designing and deploying
vector databases ,
embeddings , and
RAG architectures .
Strong knowledge of
FastAPI ,
asyncio , and microservice architectures.
Skilled with
Docker ,
Helm , and cloud-native stacks (AWS/GCP/Azure).
Excellent debugging, performance tuning, and system-level problem‑solving skills.
Demonstrated ability to deliver
high-quality code under pressure
and within
tight deadlines .
Preferred Experience
Familiarity with
LangChain ,
LlamaIndex , or other RAG frameworks.
Experience with
monitoring and observability
tools (Prometheus, Grafana, OpenTelemetry).
Contributions to
open-source AI or DevOps projects .
Understanding of
streaming systems
(Kafka, Spark, or Flink).
Education:
Bachelor’s degree (B.A.) in Computer Science, MIS or related degree
#J-18808-Ljbffr
Hybrid role based in St. Petersburg, FL
Technical Responsibilities
Architect, design, and optimize
Python-based RAG (Retrieval-Augmented Generation)
systems for real-world deployment.
Build and maintain
vector databases
and
embedding pipelines
using
Redis ,
Faiss , or similar high-performance stores.
Develop and manage
GPU-accelerated pipelines
for embedding generation and model vectorization.
Design and operate
Kubernetes (K8s)
environments for scaling distributed microservices and model workloads.
Integrate retrieval and generation components into larger
AI/LLM ecosystems
with high throughput and reliability.
Own performance tuning, profiling, and system observability for millisecond-level responsiveness.
Contribute to automation, CI/CD pipelines, and infrastructure-as-code practices.
Collaborate closely with AI engineers, data scientists, and DevOps to deliver production-grade, fault-tolerant systems.
Core Technical Qualifications
5+ years
of experience in
Python
software engineering for production systems.
Deep expertise with
Redis ,
Kubernetes , and
GPU-based computation
(CUDA, PyTorch, or TensorFlow).
Proven experience designing and deploying
vector databases ,
embeddings , and
RAG architectures .
Strong knowledge of
FastAPI ,
asyncio , and microservice architectures.
Skilled with
Docker ,
Helm , and cloud-native stacks (AWS/GCP/Azure).
Excellent debugging, performance tuning, and system-level problem‑solving skills.
Demonstrated ability to deliver
high-quality code under pressure
and within
tight deadlines .
Preferred Experience
Familiarity with
LangChain ,
LlamaIndex , or other RAG frameworks.
Experience with
monitoring and observability
tools (Prometheus, Grafana, OpenTelemetry).
Contributions to
open-source AI or DevOps projects .
Understanding of
streaming systems
(Kafka, Spark, or Flink).
Education:
Bachelor’s degree (B.A.) in Computer Science, MIS or related degree
#J-18808-Ljbffr