BackEnd Engineer

Avahi

6d•Remote

About The Position

We are seeking a highly skilled Backend Engineer to join our dynamic team. In this role, you will design, build, and maintain scalable backend systems that power advanced AI solutions for large enterprises. This is an exciting opportunity to work at the intersection of backend development and cutting-edge AI technologies, contributing to high-performance systems that integrate machine learning models, databases, and cloud services. If you are passionate about backend engineering, enjoy solving complex problems, and thrive in a fast-paced environment, we want to hear from you.

Requirements

Strong proficiency in Python, with experience designing codebases that emphasize clarity, composability, and testability over cleverness or excessive abstraction.
Solid understanding of data structures, algorithms, and backend system design, with the ability to reason about correctness, performance, and trade-offs.
Experience building systems that apply functional programming concepts in practice.
Hands-on experience with cloud platforms (preferably AWS), including compute, storage, networking, and managed data services.
Proven ability to design and build APIs and backend services, ideally within containerized environments using Docker and modern deployment pipelines.
Familiarity with large-scale or distributed systems, including asynchronous processing and service-to-service communication patterns.
A strong engineering mindset focused on writing maintainable, predictable backend code that scales across teams and over time.
Self-directed, comfortable working in fast-paced environments, and able to take ownership of complex backend systems end-to-end.
Professional-level English communication skills, with the ability to explain technical decisions clearly and concisely.

Responsibilities

Design, build, and maintain scalable backend systems for document retrieval, processing pipelines, and AI-driven integrations, prioritizing correctness, composability, and long-term maintainability.
Write backend code that minimizes side effects, structuring systems around pure transformations where possible and isolating I/O, orchestration, and infrastructure concerns at the edges.
Design and implement well-defined APIs for serving machine learning models, vector databases, and embedding services, with explicit contracts, consistent error handling, and deterministic execution paths.
Architect high-performance backend systems for AI training, simulation, and inference workloads, emphasizing clear data flow, reproducibility, and scalability.
Create internal tools and dashboards that provide visibility into backend behavior, helping teams validate assumptions, enforce invariants, and continuously improve system efficiency.
Develop automation, monitoring, and observability mechanisms that surface meaningful signals through logs, metrics, and traces, enabling rapid diagnosis of performance and reliability issues.
Build systems that integrate fine-tuned AI models with databases and downstream services using compositional design patterns rather than tightly coupled, stateful flows.
Contribute to internal tooling and open-source initiatives, ensuring codebases are easy to reason about, test, and evolve as teams and requirements grow.
Develop reusable Python libraries that integrate with AWS services and GenAI workflows, favoring small, focused functions to enable safe reuse and predictable behavior.