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.
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.
Tech Stack
AWS
Cloud
Distributed Systems
Docker
Python
Benefits
Remote-First Flexibility: Enjoy work-life harmony in a remote-first environment that allows you to work from anywhere.
Innovative Culture: We embrace a startup mindset, encouraging creativity, agility, and growth.
Career Development: Avahi is committed to your growth, offering mentorship and opportunities to advance your career, with potential for full-time roles after initial contracts.
Purpose-Driven Mission: Join us in making a difference. Avahi is dedicated to championing diversity, supporting women in tech, and fostering sustainable practices.
Global Collaboration: Work alongside a diverse, talented team, sharing insights and collaborating to create innovative solutions that make a real impact.