We are looking for a
versatile and skilled Full Stack Developer
with strong expertise in
Python ,
. NET ,
Type Script , and
PHP , along with hands‑on experience in
AWS services
(especially
Lambda
and
S3 ) and
AI/ML integration.
You’ll play a key role in designing, developing, and maintaining scalable applications and microservices, while collaborating closely with cross‑functional teams to bring innovative AI‑driven solutions to life.
Key Responsibilities
Design, develop, and maintain backend services and APIs using
Python
and
. NET (C#).
Build and optimize front‑end components using
Type Script
(React, Angular, or Vue.js).
Maintain and enhance legacy systems built in
PHP , ensuring performance and stability.
Develop, deploy, and manage
AWS Lambda
functions for serverless processing.
Integrate and manage data storage and retrieval in
AWS S3 ,
RDS , and other AWS resources.
Collaborate with AI/ML engineers to implement AI models into production environments (e.g., using AWS Sage Maker, Open AI APIs, or custom Python models).
Ensure application security, scalability, and performance across distributed systems.
Write clean, maintainable, and well‑documented code following best practices.
Participate in code reviews, technical design sessions, and agile ceremonies.
Troubleshoot, debug, and optimize application performance across environments.
Required Skills & Qualifications
Bachelor’s degree
in Computer Science, Engineering, or equivalent experience.
3–7+ years
of professional software development experience.
Strong proficiency in
Python
(Flask, Fast API, or Django).
Hands‑on experience with
. NET (C#)
for backend or microservices.
Working knowledge of
PHP
for maintaining or integrating existing systems.
Experience with
AWS Lambda ,
S3 ,
API Gateway , and other AWS services.
Familiarity with
AI/ML concepts ,
Python ML libraries
(Tensor Flow, Py Torch, scikit‑learn), or integration with
AI APIs.
Proficiency with
RESTful APIs ,
Graph QL , and
microservices architecture.
Strong understanding of
Dev Ops
and
CI/CD pipelines
(Git Hub Actions, Jenkins, or AWS Code Pipeline).
Experience with
Docker
or
Kubernetes
is a plus.
Excellent problem‑solving, debugging, and communication skills.
Preferred Qualifications
Experience deploying AI/ML models in production using
AWS Sage Maker
or
serverless AI pipelines.
Familiarity with
data pipelines ,
ETL , or
stream processing
(e.g., AWS Kinesis).
Knowledge of
infrastructure as code
(Terraform, AWS CDK, or Cloud Formation).
Contribution to open‑source projects or AI‑focused tools is a plus.
Seniority level:
Mid‑Senior level
Employment type:
Full‑time
Job function:
Information Technology
Industries:
Translation and Localization, Broadcast Media Production and Distribution, and Technology, Information and Media
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