
Back End Developer
24 hours ago
Job Title:
Backend Developer (
+ Python )
Experience:
4 to 6 Years
Employment Type:
Full-Time
Work Mode:
[On-site]
About the Role:
We're looking for a highly motivated
Backend Developer
with strong hands-on experience in
, Python
and a working knowledge of
AI/ML technologies
. You'll be part of a cross-functional team building scalable backend services that power intelligent, data-driven applications.
Key Responsibilities:
- Develop and maintain backend services using
) and
Python
(FastAPI/Django) - Build and optimize APIs (REST & GraphQL) for web and mobile products.
- Collaborate with AI/ML teams to integrate models into backend workflows.
- Work with data scientists to deploy models and manage inference pipelines.
- Design backend systems to support
AI features
such as recommendation engines, NLP, chatbots, or computer vision modules. - Write clean, maintainable, and testable code with proper documentation.
- Ensure the performance, security, and scalability of applications.
- Manage deployments using
Docker
,
CI/CD
, and cloud infrastructure (AWS/GCP/Azure). - Monitor and troubleshoot production issues proactively.
Required Skills and Qualifications:
- 4 to 6 years of backend development experience in
and
Python. - Strong knowledge of databases –
PostgreSQL
,
MongoDB
,
Redis
. - Solid understanding of
API design
,
microservices
, and system architecture. - Experience with
AI/ML integrations
– using or deploying models built with libraries like
TensorFlow
,
PyTorch
,
scikit-learn
, or
OpenAI APIs
. - Experience with
cloud services
for model hosting and serving (e.g., AWS ec2, AWS Lambda, SageMaker, GCP Vertex AI). - Experience with
containerization (Docker)
and version control (Git). - Exposure to
WebSockets
,
real-time communication
, and
message queues
(Kafka, RabbitMQ). - Working knowledge of
JWT
,
OAuth2
, and API security best practices.
Nice to Have:
- Hands-on with
LangChain
,
LLM APIs
, or
vector databases
like Pinecone or Weaviate. - Familiarity with
prompt engineering
or
LLM fine-tuning
. - Exposure to
serverless
architecture or
event-driven systems
.
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