{"id":28559,"url":"https://alion.io/job/two95-full-stack-python-developer-agentic-ai-platform","title":"Full Stack Python Developer - Agentic AI Platform","company":{"id":3423,"name":"Two95 International","domain":"two95.com","url":"https://alion.io/company/two95","size_band":"201-500","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"D","score":50,"open_postings":501,"ghost_share":0.826,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-06T05:58:05Z"}},"role":"Backend","role_family":"Backend","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["George Town, Malaysia"],"countries":["MY"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Dependency Injection","optional":false},{"name":"Docker","optional":false},{"name":"Docker Compose","optional":false},{"name":"Embeddings","optional":false},{"name":"FastAPI","optional":false},{"name":"Hybrid Search","optional":false},{"name":"JavaScript","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Pydantic","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Redis","optional":false},{"name":"Structured Outputs","optional":false},{"name":"LangChain","optional":true}],"status":"live","first_seen_at":"2026-07-31T00:00:00Z","employer_posted_date":"2026-07-31","last_verified_at":"2026-11-07T00:15:05Z","board_verified":true,"closed_at":null,"days_open":99,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":98},"description":"Job Description\nOverview\nWe 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.\nCore Hiring Bar (Non-Negotiable)\nAbility to independently read, understand, and modify moderately complex Python modules (~300+ lines)\nComfortable filling knowledge gaps through documentation and reasoning (not dependent on AI-assisted coding tools)\nDemonstrated ability to interpret existing systems and implement changes with minimal onboarding\nKey Responsibilities\nDevelop and enhance backend services and agentic workflows for the AI platform\nstateful, multi-step LLM pipelines and orchestration logic\nDesign, optimize, and maintain retrieval and scoring systems\nDebug production issues using logs, traces, and system behavior\nCollaborate across teams to deliver scalable and reliable AI-driven solutions\nImplement incremental changes with strong testing and validation practices\nTechnical Requirements\nPython (Senior Level)\nWrites clean, idiomatic Python using: \nType hints, dataclasses, Pydantic\nGenerators and context managers\nStrong understanding of: \nAsync/await and concurrency models\nProficient in Python standard libraries (e.g., pathlib, json, re, collections)\nAble to modify existing complex systems independently\nBackend Development (FastAPI)\nExperience building and extending FastAPI services\nStrong understanding of: \nRequest lifecycle\nDependency injection and middleware\nMulti-worker deployments and shared state (e.g., Redis)\nAble to diagnose issues using logs and traces (minimal debugger reliance)\nLLM Engineering (Applied)\nExperience building production-grade LLM workflows\nStrong in: \nDeterministic prompt design (structured outputs, low/no temperature)\nHandling failure modes (timeouts, malformed outputs)\nUnderstanding of RAG systems: \nChunking, embeddings, similarity scoring\nWorkflow Orchestration (LangGraph or Equivalent)\nExperience with stateful orchestration frameworks preferred\nMust be able to quickly: \nLearn graph/state concepts\nImplement multi-step workflows within 1-2 weeks\nRetrieval & Scoring Systems\nExperience with ranking/scoring methods (e.g., BM25, hybrid search)\nAbility to tune: \nThresholds, weighting, precision vs recall trade-offs\nCapable of building realistic test datasets\nDiagnostics & Log Processing\nFamiliar with log ingestion and analysis pipelines\nUnderstands: \nChunking strategies\nPattern extraction vs LLM reasoning\nWhen to use deterministic vs AI-based parsing\nInfrastructure & Runtime\nHands-on experience with: \nDocker / Docker Compose (volumes, dependencies, health checks)\nDebugging container runtime issues\nWorking knowledge of: \nRedis (basic operations, TTL, persistence)\nEnterprise networking concepts (e.g., proxies)\nFrontend (Working-Level)\nAbility to work with HTML + Vanilla JavaScript\nComfortable with: \nDOM manipulation\nFetch APIs and event handling\nAble to implement UI changes from requirements (no design dependency)\nWork Style Expectations\nStrong code-first discipline (understands design before coding)\nBuilt-in focus on: \nTesting and validation\nLog-driven debugging\nWrites clean, incremental changes with clear commits\nPerforms self-review against acceptance criteria\nAsks focused, implementation-driven questions\nExperience & Seniority\nLevel: Mid to Senior Engineer\nExperience: \n~4-8 years in Python development\nProven track record delivering production systems\nExperience with LLM-based or AI platforms preferred\nIdeal Candidate Profile\nHighly independent problem-solver\nStrong systems thinker (not just feature coder)\nComfortable working in low-AI-assist environment\nBias toward execution, debugging, and delivery 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