Job Description

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.

What You’ll Work On

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

Qualifications

What We’re Looking For

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