Backend Engineer II (Python & Distributed Systems)

About Techolution

Techolution builds custom enterprise AI that delivers measurable business results. Our FEA platform combines generative AI with cognitive decisioning to automate work at enterprise scale. Over 10 years we have served 352 enterprises across healthcare, banking, retail, insurance, government, life sciences and media, and we are a Google Cloud Premier Partner. Our teams work on real production systems for Fortune 500 clients, with a focus on AI that ships and pays back.

About the Role

As a Backend Engineer II, you will build and run the Python services behind our enterprise automation platform. Teams use it to define repeatable tasks once and reuse them: workflows generate content such as user stories and pull requests through configurable AI agents, and assessments verify that outputs are correct. The platform spans several services and code bases and supports delivery for multiple enterprise teams, so you will work on agents and the systems that compose the platform.

What You Will Do

• Design, build and maintain scalable Python backend services and APIs using async FastAPI and Flask.
• Build the agents and orchestration layer that run multi-step workflows across the platform.
• Develop background processing with Celery, and apply best practices for a shared Redis instance.
• Deploy and operate services on GCP or Azure using Kubernetes and Cloud Run, with AlloyDB or equivalent databases.
• Debug and root-cause issues across multiple services and code bases, and improve reliability through logging, monitoring and structured error handling.
• Own features end to end, from design through production rollout and long-term operation.
• Take part in design reviews and code reviews, and raise the quality bar for the team.
• Work with product managers and client-facing teams, and explain technical decisions clearly.

What You Bring

Core engineering

• Minimum 3 years of professional experience in Python-only roles. Experience in other backend languages does not count toward this requirement.
• Strong Python and object-oriented design, with a record of building maintainable, extensible services.
• Solid grounding in data structures, algorithms and problem solving.
• Experience designing, building and debugging scalable backend or distributed systems in production.
• Experience owning a system from design through production.

Backend and platform

• Production experience with async FastAPI and Flask, plus Celery or an equivalent background job framework.
• Hands-on experience building retrieval-augmented generation (RAG) systems, with an understanding of how they perform at scale.
• Experience with real-time communication using Server-Sent Events (SSE) and WebSockets.
• Hands-on cloud experience on GCP or Azure, including Kubernetes and Cloud Run or equivalents.
• Working knowledge of Redis best practices in a shared environment, and of relational databases such as AlloyDB or PostgreSQL.

Nice to Have

• Experience building AI agents, including prompt engineering and tool calling.
• Familiarity with transformer architecture beyond API-level usage.
• Experience on platform, shared infrastructure or internal tooling teams.

Interview Process

The process has four technical rounds:

• Python backend: Python depth, object-oriented design, async FastAPI and Flask, Celery, and debugging across services.
• AI and RAG: RAG pipelines, agent building and how AI components fit into backend systems.
• HLD and LLD: High-level system design and low-level design, including scalability, cloud deployment and design trade-offs.
• DSA: Data structures, algorithms and problem solving.