AI Architect

About the team:

Who you are:

• Agents in production: you've architected and operated at least one LLM agent system with real users and real traffic (tool calling, multi-step workflows, failure handling, human escalation) and owned it after launch through incidents, cost and latency. Framework demos and POCs alone won't be a fit
• Deep ML knowledge of encoders and transformers: attention, positional encodings, encoder-only vs decoder-only vs encoder-decoder, tokenization and the KV cache. You've trained or fine-tuned encoder models (BERT-family, sentence embeddings, bi-encoders, cross-encoder re-rankers) for classification, extraction or retrieval, and understand how contrastive training, distillation and quantization change cost and quality
• Context engineering:you've managed token budgets, built retrieval and memory for agents, used compaction and sub-agents to keep long tasks coherent, and measured how quality changes as the window fills
• Harness engineering: you've built the execution layer around a model: agent loop, tool dispatch, state and checkpoints, interruption and recovery, sandboxing and permissions, guardrails and model routing. Fluent with MCP, structured outputs and streaming
• Hands-on online and offline evals: you've built eval suites yourself: datasets, graders, LLM-as-judge calibration and CI regression gates offline; production scoring, trace sampling, drift monitoring, shadow deployments and feedback loops online. You've used evals to block a release or justify a model switch
• 10+ years building software or ML systems, with 3+ years building on LLMs
• Python: strong, hands-on. Comfortable reading and reviewing Java or TypeScript services
• Production experience on AWS or GCP, containers and Kubernetes, and event-driven systems
• Excellent oral and written communication skills: you can explain a trade-off to an engineer and its business impact to an executive

Nice to have:

• Experience in supply chain, logistics or transportation
• Document AI: OCR, layout models, and extraction from bills of lading, invoices and PODs
• Voice or email agents that act on behalf of a business
• Agent security: prompt injection defence, tool permissioning, and tenant data isolation
• Hands-on experience with several model families (Claude, GPT, Gemini, open-weight models) and serving stacks
• Published work, talks or open-source contributions on agents, retrieval or evaluation

Who we are:

Benefits:

• Medical benefits start on first day of employment
• 36 PTO days (Sick, Casual and Earned), 5 recharge days, 2 volunteer days
• Home Office set ups and Technology reimbursement
• Lifestyle & Family benefits
• Mental Wellness support and guidance
• Ongoing learning & development opportunities (Professional development program, Toast Master club, etc.)
• FourKites is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.