Python Developer - Agentic AI Platform

Two95 International · George Town

Overview

We are hiring a Mid-to-Senior Full Stack Developer to build and extend an Agentic AI platform with strong focus on LLM workflows, orchestration, and backend systems. This role requires a highly independent engineer who can quickly understand existing codebases and deliver production-quality enhancements with minimal guidance.

Core Hiring Bar (Non-Negotiable)

Ability to independently read, understand, and modify moderately complex Python modules (~300+ lines)
Comfortable filling knowledge gaps through documentation and reasoning (not dependent on AI-assisted coding tools)
Demonstrated ability to interpret existing systems and implement changes with minimal onboarding

Key Responsibilities

Develop and enhance backend services and agentic workflows for the AI platform
Build stateful, multi-step LLM pipelines and orchestration logic
Design, optimize, and maintain retrieval and scoring systems
Debug production issues using logs, traces, and system behavior
Collaborate across teams to deliver scalable and reliable AI-driven solutions
Implement incremental changes with strong testing and validation practices

Technical Requirements

Python (Senior Level)

Writes clean, idiomatic Python using:

Type hints, dataclasses, Pydantic
Generators and context managers

Strong understanding of:

Async/await and concurrency models

Proficient in Python standard libraries (e.g., pathlib, json, re, collections)
Able to modify existing complex systems independently

Backend Development (FastAPI)

Experience building and extending FastAPI services
Strong understanding of:

Request lifecycle
Dependency injection and middleware
Multi-worker deployments and shared state (e.g., Redis)

Able to diagnose issues using logs and traces (minimal debugger reliance)

LLM Engineering (Applied)

Experience building production-grade LLM workflows
Strong in:

Deterministic prompt design (structured outputs, low/no temperature)
Handling failure modes (timeouts, malformed outputs)

Understanding of RAG systems:

Chunking, embeddings, similarity scoring

Workflow Orchestration (LangGraph or Equivalent)

Experience with stateful orchestration frameworks preferred
Must be able to quickly:

Learn graph/state concepts
Implement multi-step workflows within 1–2 weeks

Retrieval & Scoring Systems

Experience with ranking/scoring methods (e.g., BM25, hybrid search)
Ability to tune:

Thresholds, weighting, precision vs recall trade-offs

Capable of building realistic test datasets

Diagnostics & Log Processing

Familiar with log ingestion and analysis pipelines
Understands:

Chunking strategies
Pattern extraction vs LLM reasoning
When to use deterministic vs AI-based parsing

Infrastructure & Runtime

Hands-on experience with:

Docker / Docker Compose (volumes, dependencies, health checks)
Debugging container runtime issues

Working knowledge of:

Redis (basic operations, TTL, persistence)
Enterprise networking concepts (e.g., proxies)

Frontend (Working-Level)

Ability to work with HTML + Vanilla JavaScript
Comfortable with:

DOM manipulation
Fetch APIs and event handling

Able to implement UI changes from requirements (no design dependency)

Work Style Expectations

Strong code-first discipline (understands design before coding)
Built-in focus on:

Testing and validation
Log-driven debugging

Writes clean, incremental changes with clear commits
Performs self-review against acceptance criteria
Asks focused, implementation-driven questions

Experience & Seniority

Level: Mid to Senior Engineer
Experience:

~4–8 years in Python development
Proven track record delivering production systems
Experience with LLM-based or AI platforms preferred

Ideal Candidate Profile

Highly independent problem-solver
Strong systems thinker (not just feature coder)
Comfortable working in low-AI-assist environment
Bias toward execution, debugging, and delivery quality

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