Senior Software Engineer (Python) — AI Platform & Distributed Systems

About the Role

We are looking for a highly skilled

Backend Engineer

with a strong background in

Python, system design, and infrastructure

to join our team. You will be responsible for designing, building, and maintaining scalable backend systems, while collaborating with cross-functional teams to deliver robust and efficient solutions.

This role requires someone who can think

end-to-end

, from designing high-level architecture, implementing core services, to ensuring production-grade reliability and performance.

Key Responsibilities

Develop and maintain backend services and APIs using

Python

NodeJs

Design scalable, resilient, and maintainable systems, focusing on

system architecture and distributed systems

Integrate

AI and large language models (LLMs)

into applications, ensuring performance, scalability, and cost-efficiency.

Collaborate with AI / ML teams to deploy models into production pipelines.

Optimize infrastructure for AI workloads (GPU usage, caching, batch processing)

Build and maintain

monitoring, logging, and observability

for AI-powered systems.

Troubleshoot and resolve issues in production systems while maintaining high reliability.

Participate in design and code reviews, and drive engineering best practices across the team.

Automate deployment pipelines for backend and AI services (CI / CD, IaC).

Required Skills & Qualifications

Strong experience in

Python

(FastAPI (most-preferred), Flask, Django, or similar) or

NodeJS

(Express (most-preferred), Fastify or similar)

Solid understanding of

system design principles

: scalability, fault tolerance, distributed systems.

Experience with

infrastructure and DevOps

: Docker, Kubernetes, Terraform, CI / CD pipelines.

Hands-on experience with

cloud platforms

(AWS, Azure, GCP), especially for AI workloads.

Knowledge of

databases

(SQL & NoSQL) and caching systems (Redis, Memcached).

Experience integrating

LLMs

or AI APIs into production systems (OpenAI, HuggingFace, LangChain, etc.).

Familiarity with

messaging / streaming systems

(Kafka, RabbitMQ).

Monitoring and observability experience (Prometheus, Grafana, ELK).

Strong problem-solving, debugging, and analytical skills.

Excellent communication and collaboration skills.

Nice to Have

Experience with

generative AI pipelines

, vector databases, and embeddings.

Familiarity with

ML Ops tools

(MLflow, BentoML, Ray Serve, etc.).

Knowledge of

event-driven architectures

and microservices.

Prior experience in

AI / LLM-focused startups or high-scale AI systems

What We Offer

Opportunity to work on

challenging, large-scale systems

with real-world impact.

Collaborative team culture with focus on

learning and innovation

Competitive compensation and growth opportunities.