Python Developer - Agentic AI Platform
At a glance
Mid-level ML Platform & Ops role at Two95 International Inc. George Town.
Pay not stated ML Platform & Ops salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build backend services and agent workflows, including stateful LLM pipelines and their orchestration
- Maintain retrieval and scoring systems, tuning rankings and balancing precision against recall
- Investigate production failures through logs, traces and system behavior, then make tested changes
- Extend platform services and workflows with incremental code changes and validation
What you bring
- Around four to eight years developing in Python, with a record of shipping production systems
- You can independently read and change moderately complex Python modules, using documentation and reasoning to fill gaps
- You have built FastAPI services and applied LLM workflows, including retrieval-augmented systems
- You can debug Python services using logs and traces, and work with Docker and Redis
Who this fits
This suits an independent, mid-to-senior engineer who can understand existing systems quickly and deliver with limited guidance. You'll need to work onsite in George Town, Malaysia. The role covers backend and AI workflows as well as working-level HTML and vanilla JavaScript.
From the employer
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