Forward Deployed Engineer

Kinaxis

Forward Deployed Engineer developing and deploying customer solutions on the Kinaxis Maestro Platform. Collaborating with customers to enhance supply chain operations through AI technology.

Posted 6/30/2026full-timeRemote • California, New York • 🇺🇸 United StatesJuniorMid-LevelWebsite

Tech Stack

Tools & technologies

AirflowBigQueryKafkaPython

About the role

Key responsibilities & impact

Own customer solutions end-to-end
Rapidly prototype, iterate, and deploy solutions in live operational environments where the stakes are real and the timeline is short
Deliver relentless customer value
Build trusted relationships from the IC level to the executive sponsor and become the technical face of our company in the room
Run multiple threads
Carry several customer engagements in parallel based on customer priorities and pod capacity
Set expectations early, renegotiate honestly when reality shifts, operate without close supervision, and own the outcome
Operate as a SEAL team
Make the product better
Partner with Product and Engineering to convert field learnings into durable platform capabilities not one-off scripts
Drive adoption and lead the change
Mentor customer operators and guide their teams through solution transitions, so the new way of working actually sticks

Requirements

What you’ll need

AI & Agentic Development
Hands-on experience building LLM-based applications, RAG systems, multi-agent workflows, tool-use patterns, prompt and context engineering
Familiarity with modern AI-assisted development tools (Copilot, Claude Code, agentic IDE workflows)
Understanding of agentic orchestration patterns when to use single vs. multi-agent architectures, how to handle memory and state
Solid, hands-on software engineering fundamentals: you have built and shipped real systems, not just scripts
Proficiency in at least one backend language (Python strongly preferred) and the ability to read and contribute across a polyglot codebase
Experience with REST and streaming APIs, authentication patterns, and integration with enterprise systems
Ability to build and maintain data pipelines ingestion, transformation, serving, and monitoring using tools such as Airflow, Kafka, dbt, or equivalents
Working familiarity with modern data platforms (Snowflake, Databricks, BigQuery, or similar), including data modeling and performance fundamentals
Strong debugging instincts with imperfect, real-world data in production environments
Prior exposure to supply chain planning, logistics, or operations domains is a genuine plus not a requirement
2 – 5 years of professional experience in software engineering, data engineering, solutions engineering, or a technical-founder role
Prior exposure to customer-facing technical roles solutions engineering, forward deployment, technical consulting, or a startup where you wore multiple hats is a strong signal, though not a requirement

Benefits

Comp & perks

Flexible vacation and Kinaxis Days (company-wide days off)
Flexible work options
Physical and mental well-being programs
Regularly scheduled virtual fitness classes
Mentorship programs, training, and career development
Recognition programs and referral rewards
Hackathons

ATS Keywords

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Hard Skills & Tools

LLM-Based ApplicationsMulti-Agent WorkflowsPrompt EngineeringREST APIsStreaming APIsData IngestionData TransformationData ServingData MonitoringSoftware Engineering Fundamentals

Soft Skills

Customer Relationship BuildingMentoringExpectation ManagementAdaptabilityCollaboration