Software Engineer
Company Description:
The Ikigai platform unlocks the power of generative AI for tabular data. We enable business users to connect disparate data, leverage no-code AI/ML, and build enterprise-wide AI apps in just a few clicks. Ikigai is built on top of its three proprietary foundation blocks developed from years of MIT research - aiMatch, for data reconciliation, aiCast, for prediction, and aiPlan, for scenario planning and optimization. Our platform enables eXpert-in-The-Loop (XiTL) for model reinforcement learning and refinement, at scale.
Rooted in academia, Ikigai also offers unmatched educational support that upskills workforces and transforms organizations into AI-driven ones. Ikigai Academy has already trained over 6000 students from +0+ countries on topics like “No Code AI” and “Time Series Forecasting”.
Role Description:
Ikigai Labs is seeking a dynamic and passionate engineer with strong software fundamentals to join a high-performing infrastructure team. We are looking for a team player who is a quick learner, performs in a rapid development cycle, has a drive to surpass expectations, and an eagerness to share their work and knowledge.
Responsibilities:
Design and develop scalable data integration (ETL/ELT) processes
Improve and optimize an on-demand predictive modeling platform with Python
Utilize Kubernetes to orchestrate scalable deployments and manage Docker containers
Learn and leverage numerous AWS services to solve cloud-native problems, improve the testing platform which performs sanity checks, unit tests, scale tests, heartbeat tests, and performance tests
Work to keep the platform secure and follow industry standard compliance practices (ISO 27001:2022 and SOC II + HIPAA)
Provide periodic support to our customer success team
Technologies:
Languages: Python3, SQL, GoLang, bash
Cloud: Kubernetes, Helm, EKS, Terraform, AWS
Databases: Postgres, Elasticsearch, DynamoDB
Data Engineering: Apache Arrow, Dremio, Ray
Misc.: Apache Superset, GRPC, Jenkins, Airbyte
Qualifications:
A bachelor's/master’s degree in Computer Science or Engineering
Must have advanced experience with Python, AWS services, and/or ETL/ELT pipelines
Experience with Kubernetes and/or EKS/AKS (optional)
Understanding fundamentals of system design patterns and testing best practices
The ability to learn quickly in a fast-paced environment
Excellent organizational, time management, and communication skills
Willingness to discuss obstacles, find creative solutions, and take initiative
The ability to receive and give both constructive and encouraging feedback
Knowledge of streaming data processing and real-time analytics.
Familiarity with data governance, security, and compliance best practices