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Knowledge Engineer
Automate complex decision-making in regulated industries using deterministic symbolic reasoning to eliminate hallucinations and ensure full auditability.
Benefits:
Competitive package based on experience
Training and support to become an AI expert
Flexible working policy
Friendly and collaborative team
Access to market leading technology
Experience Requirements:
Expertise in business analysis
Experience in process modelling or BPM
Stakeholder management and client engagement
Experience working with APIs (REST/JSON)
Experience working in an agile environment
Other Requirements:
Understanding of knowledge graphs and semantic technologies
Familiarity with Large Language Models (LLMs)
Skilled in documentation and report writing
Ability to travel (up to 10%)
Responsibilities:
Capture and interpret business knowledge to develop AI models
Engage with clients to implement Rainbird in projects
Discover and document project blueprints and 'excelerators'
Build field demos, PoCs, and pilots for sales
Deliver coaching and training to clients and partners
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Solutions Engineer
Automate complex decision-making in regulated industries using deterministic symbolic reasoning to eliminate hallucinations and ensure full auditability.
Benefits:
Competitive package
Remote work with flexible arrangements
Innovative and collaborative scale-up culture
Shape customer platform interaction
Work at intersection of AI and enterprise automation
Experience Requirements:
Previous experience in a customer-facing technical role
Experience designing and implementing technical solutions
Proficiency in Python, JavaScript/Node.js, or Go
Practical experience with cloud platforms (AWS, GCP, Azure)
Experience with data transformation and ETL processes
Other Requirements:
Knowledge of API development and RESTful services
Understanding of authentication protocols (OAuth, JWT)
Experience with containerization (Docker, Kubernetes)
Exceptional communication skills
Responsibilities:
Design and deliver seamless integrations for client ecosystems
Translate ambiguous requirements into tangible solutions
Implement integration architectures and custom data layers
Build connectors and middleware for third-party systems
Develop proof-of-concept implementations and technical prototypes
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