Drive complex, cross-functional technical projects from conception to deployment, defining technical strategy and architecture for major systems and products.
Make impactful technical decisions across multiple teams, mentor other engineers, and foster a culture of engineering excellence.
Collaborate closely with product managers, designers, and stakeholders, champion innovation, and embody Kantata’s core values.
Identify and solve critical and ambiguous technical challenges; design scalable, reliable, and maintainable systems.
Create architectural blueprints and technical roadmaps; partner with product managers and stakeholders to define technical requirements.
Influence product direction based on technical feasibility and opportunities; research and evaluate new technologies, tools, and methodologies.
Write high-quality, exemplary code that serves as a model for others and debug/resolve the most complex technical issues.

Requirements

10+ years of functional experience, including at least 5 years in a technical leadership role.
Expertise in system design, architecture, and technical strategy for large-scale products.
Advanced proficiency in relevant programming languages, frameworks, and tools.
Experience ensuring performance, security, and reliability in complex systems.
Strong communication skills, able to convey technical concepts to diverse audiences.
Demonstrated commitment to innovation, continuous improvement, and engineering best practices.
Proven ability to troubleshoot, debug, and optimize system performance, ensuring the reliability and efficiency of engineering solutions.
Deep experience with modern graph database systems (e.g., Neo4j, TigerGraph, AWS Neptune, ArangoDB, JanusGraph).
Expert-level knowledge of building reliable, scalable data pipelines (using tools like Kafka, Spark, Airflow).
Practical experience with techniques like Named Entity Recognition (NER), Relationship Extraction (RE), and Text Classification.
Experience with vector embeddings and vector stores (e.g., Pinecone, Milvus, Chroma).
Experience in deploying, monitoring, and scaling ML models in production (e.g., using SageMaker, MLflow).
Direct, hands-on experience designing, developing, and deploying AI agents and multi-agent systems.
Proficiency with modern agent orchestration frameworks (e.g., LangChain, Microsoft AutoGen, CrewAI, Haystack).

Benefits

An intentionally engaging and collaborative culture - ditch the silo!
Strong work-life balance that’s a true focus of the company
The chance to learn from some of the best people in the business
A vibrant, collaborative and devoted team, who still makes time for fun

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

system designarchitecturetechnical strategyprogramming languagesgraph database systemsdata pipelinesNamed Entity RecognitionRelationship ExtractionText ClassificationML model deployment

Soft Skills

communication skillsmentoringinnovationcontinuous improvementengineering best practicesproblem-solvingcollaborationleadershiptechnical decision-makingfostering culture of excellence