Forward Deployed Engineer building and deploying agentic AI solutions on Kinaxis Maestro. Helping global supply-chain customers improve operational outcomes and adopt new workflows.
Responsibilities
Own customer solutions end-to-end by rapidly prototyping, iterating, and deploying solutions in live operational environments
Build trusted customer relationships from individual contributors to executive sponsors and serve as the technical face of Kinaxis
Manage multiple customer engagements in parallel based on customer priorities and pod capacity
Operate in a small, multidisciplinary, self-directed POD team
Partner with Product and Engineering to turn field learnings into durable platform capabilities
Mentor customer operators and guide teams through solution transitions and adoption
Measure success through business outcomes such as efficiency gains, exception reduction, and SLA improvements
Bring field learnings back into the platform and help create scalable capabilities
Requirements
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, including Copilot, Claude Code, and agentic IDE workflows
Understanding of agentic orchestration patterns, including single- versus multi-agent architectures and handling memory and state
Solid, hands-on software engineering fundamentals and experience building and shipping real systems
Proficiency in at least one backend language; Python strongly preferred
Ability to read and contribute across a polyglot codebase
Experience with REST and streaming APIs, authentication patterns, and enterprise-system integration
Ability to build and maintain data pipelines for ingestion, transformation, serving, and monitoring using Airflow, Kafka, dbt, or equivalents
Working familiarity with modern data platforms such as Snowflake, Databricks, BigQuery, or similar
Data modeling and performance fundamentals
Strong debugging instincts with imperfect, real-world data in production environments
2–5 years of professional experience in software engineering, data engineering, solutions engineering, or a technical-founder role
Customer-facing technical experience is a strong signal, though not a requirement
Ability to travel as required, up to 50%
Benefits
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
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