Senior Python Backend Engineer

4 days ago

Rajkot, Gujarat, India 𝐐𝐰𝐢𝐧𝐭𝐒𝐨𝐟𝐭 Full time ₹ 20,00,000 - ₹ 25,00,000 per year

About the Role

We are seeking a highly experienced
Senior Python Backend Engineer

to design, build, and scale backend services for our global art information platform. In this role, you will work on integrating advanced
AI/ML models

into production systems, powering features such as recommendations, personalization, and intelligent search.

This position is ideal for someone passionate about backend engineering and excited to bring
AI-powered user experiences

to life at scale. Experience in recommendation systems is a strong advantage but not a strict requirement.

Responsibilities

  • Design, build, and maintain robust backend services in
    Python

(FastAPI, Django, or Flask).
- Integrate
machine learning models

into production APIs and pipelines for recommendations and personalization.
- Collaborate closely with ML engineers and product teams to deliver
AI-driven features

.
- Develop
low-latency APIs

for serving recommendations and intelligent results.
- Work with
vector databases

(Qdrant, Pinecone, Elasticsearch, etc.) to power similarity search and embeddings.
- Deploy, monitor, and scale services in
cloud environments

(AWS preferred).
- Contribute to
system architecture, performance optimization, and design decisions

.
- Implement
CI/CD pipelines

with strong testing and code quality practices.

Requirements

  • Strong understanding of
    backend architecture

and distributed systems.
- Proven track record of building and deploying
production-ready APIs

.
- Experience integrating
ML models or AI services

into backend infrastructure.
- Hands-on expertise with
cloud platforms

(AWS preferred) and DevOps tools (Docker, Kubernetes, Terraform).
- Database expertise:
SQL (PostgreSQL/MySQL)

and
NoSQL (Redis, Elasticsearch)

.
- Excellent communication and collaboration skills in remote team settings.

Nice to Have (Bonus Skills)

  • Experience with
    recommendation systems

or personalization pipelines.
- Familiarity with
vector databases

and
embedding-based search

.
- Frontend integration knowledge (React, , GraphQL).
- Experience monitoring and optimizing
ML-powered production systems

(Prometheus, Grafana).

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