Job Overview

Location
Karachi, Sindh
Job Type
Full Time
Date Posted
6 hours ago

Additional Details

Job ID
2125
Job Views
15
Work Mode *
On-site

Job Description

Senior Backend Engineer - Platform & Infrastructure


Company Description:

Lambda Theta specializes in designing and developing AI-powered software solutions for international clients. With expertise in computer vision, natural language processing (NLP), artificial intelligence, and embedded systems, we deliver state-of-the-art, customized solutions that address complex industry challenges. Our focus is on building highly specialized and indigenized software systems tailored to client needs.


Key Responsibilities:

API Gateway & Load Balancing: Design and implement robust API gateway solutions with load balancing, rate limiting, SSL termination, and DDoS protection

Session & Cache Management: Build scalable session management systems with multi-level caching strategies (L1 in-chat, L2 shared, L3 distributed)

Task Orchestration: Develop sophisticated task queuing, scheduling, and distribution systems for parallel processing workflows

System Architecture: Design microservices architecture with proper service mesh, inter-service communication, and fault tolerance

Performance Optimization: Implement auto-scaling, resource optimization, and system performance monitoring

Security & Compliance: Ensure authentication, authorization, data encryption, and security best practices


Required Technical Skills:

Languages: Python (advanced), Go/Java (preferred for high-performance services)

Frameworks: FastAPI/Flask, Django, or equivalent web frameworks

Databases: PostgreSQL, Redis, MongoDB (multi-database experience), Milvus

Message Queues: RabbitMQ, Apache Kafka

Containerization: Docker, Kubernetes (production experience required)

Cloud Platforms: OCI/GCP/Azure (at least one, OCI)

API Design: RESTful APIs, GraphQL, API versioning and documentation

Monitoring: Prometheus, Grafana, ELK stack, distributed tracing


Domain-Specific Requirements:

Experience with ML pipeline orchestration (Airflow, Prefect, or similar)

Understanding of model serving frameworks (MLflow, KubeFlow, Seldon)

Experience with high-throughput, low-latency systems

Familiarity with observability in ML systems


Location

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