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Tech Stack
Tools & technologiesAzurePython
About the role
Key responsibilities & impact- Design and ship production AI systems — multi-agent orchestration, routing, and specialized agents that take a request and carry it through to a reliable outcome.
- Automate manual operational work across onboarding, support, exceptions, and document/data understanding — turning processes that take hours or days into seconds.
- Build the models behind the decisions — forecasting, prediction, matching/allocation, optimization, and reliability scoring that ground the product in data instead of guesswork, exposed as services the agent layer can call.
- Design the learning loop. Instrument decisions and their outcomes so models continuously improve, with the data and evaluation infrastructure to support it.
- Own reliability and evaluation. Build the eval harnesses, tracing, observability, and guardrails for complex AI workflows where mistakes carry real operational and financial consequences — and prove a model or agent beats the status quo before it ships.
- Make the build-vs-rules calls — know when a model genuinely wins, when an agent is the right tool, and when a simple rule is the smarter answer.
- Raise the bar and help the team grow — push our prototyping-to-production pipeline forward and mentor engineers as the AI team scales.
Requirements
What you’ll need- You've shipped production AI/ML, not just prototypes — and dealt with the real tradeoffs of edge cases, quality, latency, cost, and reliability.
- You have real depth on at least one of these, and working fluency across both:
- - Generative / agentic AI — multi-agent orchestration, tool/function calling, RAG, structured outputs, and the modern stack (e.g., LangGraph/LangChain, MCP), across providers (Amazon Bedrock, Azure OpenAI, Anthropic, OpenAI).
- - Applied ML / decision intelligence — forecasting, optimization, matching/allocation, ranking, or prediction models that drive operational decisions with measurable business impact.
- You design and trust your own evaluation — offline and online, tied to business outcomes, with safe rollout (e.g., shadow mode) and drift monitoring.
- You're deeply hands-on and ship fast — strong in Python, modern API/services (e.g., FastAPI), and sound ML-systems and architecture instincts.
- You've built for operationally complex or high-stakes environments where quality and reliability genuinely matter.
- You communicate clearly, make decisions quickly, and can lead technical work without needing heavy process.
- Bonus points:
- - Background in logistics, supply chain, transportation, marketplaces, mobility, or fulfillment.
- - Operations research / optimization, or reinforcement learning / bandits for sequential decision-making.
- - Multimodal / document understanding, computer-use, or browser automation.
- - Real-time / streaming systems, feature stores, and production MLOps at scale.
- - Patents or peer-reviewed publications, or experience as an early/founding engineer.
Benefits
Comp & perks- Competitive salary, stock options, and performance-based bonuses
- Fully remote
- Comprehensive medical, vision, and dental insurance
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI systems designmulti-agent orchestrationroutingforecastingprediction modelsoptimizationPythonFastAPIevaluation infrastructureMLOps
Soft Skills
clear communicationdecision makingleadershipmentoringproblem solvingteam collaborationadaptabilitycritical thinkingtime managementprocess improvement