Junior FDE (AI & Backend)

About the Role

This is a build-and-learn role focused on AI-native products. You will work from tickets scoped by a senior engineer, with code review on every change, and grow into owning full features. The team utilizes an AI-assisted workflow with agentic AI coding tools.

Key Responsibilities

• Own scoped tickets end-to-end:
• Build DRF endpoints and models.
• Implement individual LLM workflows (prompts, tool calls, MCP tools).
• Fix bugs from logs and traces.
• Test shipped code and incorporate feedback from code reviews.
• Workload breakdown:
• Backend features & APIs (~35%): DRF models, serializers, viewsets, migrations on PostgreSQL.
• LLM workflows, skills & MCP connectors (~25%): Prompts, tool use, agent skills, custom MCP tools/connectors.
• Async jobs & integrations (~15%): Celery/Redis tasks, third-party APIs, auth (JWT/OAuth2).
• Bugs & debugging (~15%): Identifying and resolving issues.
• Tests, review & light frontend (~10%): pytest, PR cycles, small React/Next.js fixes.
• Flag blockers early, ask before guessing, and escalate critical issues (auth, data, production) to a senior.

Requirements & Tech Stack

• AI/LLM Engineering:
• Anthropic API
• MCP (Model Context Protocol)
• Agentic AI coding tools (CLI/IDE)
• Reusable agent skills (SKILL.md-style)
• Custom agents/subagents
• Custom MCP connector creation
• Prompt engineering
• Basic LLM agent concepts
• Optional: OpenAI API, RAG pipelines
• Backend:
• Python
• Django
• Django REST Framework (DRF)
• PostgreSQL
• Celery
• Redis
• JWT/OAuth2
• Docker
• DevOps/Tools:
• Azure
• Git
• CI/CD
• Optional: Sentry, AWS
• Testing & Quality:
• Optional: pytest, TDD
• Frontend:
• React/Next.js
• TypeScript
• REST API integration

Qualifications

• Must-have:
• Python + Django/DRF fundamentals (0–2 years hands-on experience).
• SQL & PostgreSQL: basic relational modelling, joins, indexes.
• LLM API experience: built at least one project calling an LLM API (Anthropic preferred) with tool/function calling.
• Skills, agents & MCP basics: written at least one agent skill or custom agent/subagent, and built a simple custom MCP server/connector.
• API basics: REST design, JWT/OAuth2 authentication, Docker basics.
• Git discipline: branching, pull requests, resolving conflicts.
• Communication: clear written updates, early escalation of blockers, receptiveness to review feedback.
• Strongly preferred:
• Daily use of agentic AI coding tools.
• Custom MCP connector creation for real APIs.
• Authored agent skills or configured custom agents.
• Experience with Celery/Redis for background jobs.
• React/Next.js + TypeScript for UI work.
• Nice-to-have:
• pytest and TDD habits.
• Azure or AWS basics.
• Sentry.
• RAG pipelines.
• B.E./B.Tech/MCA/BCA in CS or equivalent proof of work.

Evaluation focus is on Python/Django fundamentals, problem-solving, and real LLM projects.