Intermediate Backend Software Developer

Role Overview

Triton Digital is hiring an Intermediate Backend Software Developer to help build and evolve backend infrastructure for its product suite, with a strong focus on an AI chatbot assistant. The role blends traditional backend engineering with production-grade AI system development (e.g., RAG, multi-step agent workflows, tool calling, memory/state management, and LLM integrations).

Responsibilities

• Design, build, and maintain scalable RESTful/GraphQL APIs and microservices for the AI chatbot and related backend systems.
• Implement agentic AI systems (e.g., LangChain/LangGraph or equivalent) including:
  • multi-agent orchestration
  • tool calling to external APIs
  • reasoning loops
  • memory and state management
• Integrate with third-party LLM providers; handle prompting, rate limiting, cost optimization, and fallback logic.
• Build and optimize RAG pipelines, including:
  • document ingestion
  • embeddings generation
  • vector search/retrieval
  • context-aware response generation
• Work with relational and NoSQL databases as well as vector databases.
• Build reliable integrations with external services via APIs, webhooks, and event-driven patterns.
• Ensure high availability, performance, security, observability, and scalability through monitoring/logging, caching, and async processing.
• Write clean, testable, well-documented code; participate in code reviews, architecture discussions, and agile ceremonies.
• Collaborate with engineering teams and product stakeholders to deliver end-to-end features.

Additional Responsibilities

• Develop/configure and maintain cloud infrastructure.
• Participate in a 24/7 on-call rotation for team-owned projects.

Required Qualifications

• 5+ years of hands-on backend development experience.
• Strong Python skills with modern Python web frameworks (FastAPI, Django, or Flask preferred).
• Solid knowledge of relational and NoSQL databases, ORM/query optimization, and data modeling.
• Experience with REST, GraphQL, or event-driven architectures (e.g., Kafka, RabbitMQ).
• Familiarity with cloud platforms (AWS, GCP, or Azure), including serverless, Docker, and basic orchestration (Kubernetes or similar).
• Working knowledge of AI integration concepts: LLMs, embeddings, vector search, RAG, and basic prompt/tool-calling.
• Strong engineering fundamentals: clean code, testing (unit/integration), CI/CD, Git, and Agile.
• Ability to break down complex AI requirements into robust backend solutions.
• Observability and security familiarity (e.g., Prometheus/Grafana/Datadog/OpenTelemetry, OAuth/JWT/API gateways).
• Advanced English communication skills.

Highly Preferred / Nice to Have

• Direct experience building/contributing to RAG systems or agentic workflows (LangChain/LangGraph, LlamaIndex, Haystack, CrewAI, AutoGen, etc.).
• Experience with function/tool calling, structured output parsing, and multi-step agent reasoning.
• Knowledge of Java/Spring Boot.
• Understanding of LLM cost/performance trade-offs and prompt engineering.
• Bachelor’s degree in Computer Science/Engineering or equivalent experience.