AI Engineer

Responsibilities

• AI‑Native & Agent‑First Development
• Design and build LLM‑driven agents to support planning, optimization, and decision‑making workflows
• Develop agent orchestration patterns (tools, memory, evaluation, guardrails)
• Build and maintain RAG pipelines , structured prompting, and retrieval strategies
• Treat simulation as a first‑class design tool (using synthetic data, scenario replay, and state machines to validate logic)
• Fullstack Product Engineering
• Build end‑to‑end product features spanning: Backend services (Python / TypeScript)
• APIs (REST / GraphQL / FastAPI)
• Frontend experiences (React)
• Create human‑in‑the‑loop interfaces for AI systems (review, override, explainability)
• Collaborate closely with Product and Design to ship usable, explainable AI features
• Platform & Engineering Quality
• Own services in production: performance, reliability, observability, and cost
• Design systems that are secure, testable, and compliant by default
• Use infrastructure‑as‑code and modern CI/CD practices
• Champion simulation‑led design , testability, and fast feedback loops
• What Success Looks Like (6-12 Months)
• AI agents are shipping as core product capabilities , not experiments
• Simulation and synthetic data are actively used to design and validate features
• Product teams can move faster because AI systems are observable, testable, and trusted
• Engineering quality improves without slowing delivery
• Why IFS.ai Logistics
• IFS.ai Logistics is building the next generation of logistics optimization software - combining AI, simulation, and human expertise to reduce cost, emissions, and complexity in global supply chains.
• You'll work on hard problems , with real‑world impact , alongside a team that values design‑led thinking, technical depth, and autonomy .

Requirements

• Core Experience
• We are looking for an AI Engineer with a minimum of 5 years of hands-on, relevant industry experience
• Strong fullstack engineer with deep backend capability
• Production experience with Python, including solid experience building backend systems using Django.
• Experience owning systems from concept to production
• Comfortable working in small, high‑ownership teams
• AI & Data (Practical, Not Theoretical)
• Hands‑on experience with: LLMs and modern AI tooling
• RAG systems, embeddings, vector search
• Agentic patterns (tools, planners, evaluators)
• Experience productionising ML/AI systems (monitoring, failure modes, iteration)
• Pragmatic mindset: understands where AI adds value - and where it doesn't
• Ways of Working
• Agent‑first, spec‑driven , or simulation‑led mindset
• Comfortable operating with ambiguity
• Strong collaborator with Product, Design, and other engineers
• Bias toward shipping , learning, and iterating
• Nice to Have (But Not Required)
• Experience with logistics, optimization, or simulation‑heavy domains
• Background in data engineering or ML platforms
• Experience building developer tools or internal platforms
• Exposure to regulated or security‑conscious environments
• Tech Stack
• Backend: Python (Django, FastAPI), TypeScript (Node.js)
• Frontend: React
• AI: LLMs, RAG pipelines, agent frameworks
• Infra: Cloud (AWS / GCP), Docker, CI/CD, IaC
• Data: SQL, event‑driven systems, analytics pipelines

Additional Information

Role Summary We are looking for a AI (Fullstack) Engineer to help evolve IFS.ai Logistics into an agent‑first, AI‑native product . This is not a traditional "add AI to an existing system" role. You will design and build LLM‑powered agents , simulation‑driven workflows , and AI‑native product capabilities that sit at the core of our logistics optimization platform. You will work across frontend, backend, data, and infrastructure , owning problems end‑to‑end and shaping how we build software - not just what we build.

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