Jobs at Koantek

Coordinate high-volume interviews across time zones, manage candidate communications and logistics, maintain ATS records and interviewer feedback, post jobs, initiate background checks, support offer letters, and facilitate handoffs to onboarding and People Operations.

Manage cloud data projects end to end, overseeing scope, budget, timelines, resources, risks, quality, governance, and stakeholder communication. Lead cross-functional teams of data engineers and data scientists, coordinate cloud architecture implementation, establish reporting and mitigation processes, and ensure successful delivery of data migration, data lake, data warehouse, data engineering, and data science engagements.

Design, build, and productionize large-scale machine learning, generative AI, and agentic systems. Own the complete AI product lifecycle from experimentation through production deployment, implementing MLOps workflows with MLflow and Databricks to ensure reliability, scalability, monitoring, and performance. The role requires proven model productionization experience and expertise in Databricks technologies, agent development frameworks, and software repository management.

Design, build, and deploy modern Single Page Applications and scalable backend services. Develop REST APIs, integrate with PostgreSQL, implement authentication, testing, and deployment practices, collaborate with engineers and stakeholders, and take ownership from concept to production.

Lead end-to-end ML implementations for clients, design and maintain production-grade MLOps pipelines, deploy and optimize Generative AI/LLM and NLP solutions, manage infrastructure (Docker, orchestration, distributed compute), and communicate technical results to stakeholders.

Design, build, and maintain end-to-end data pipelines and ETL/ELT processes on Databricks (Azure). Implement Spark (PySpark/Scala) transformations, manage Delta Lake/Unity Catalog, integrate varied data sources (APIs, databases, IoT), and support analytics via APIs and data services. Ensure data quality, security, CI/CD, and performance optimization while collaborating with cross-functional teams to deliver scalable BI and reporting solutions.

Lead design and delivery of enterprise Databricks Lakehouse architectures, implement and optimize large-scale Spark data pipelines, advise clients on governance, security, MLOps and cloud integration, and provide workshops and mentorship to accelerate adoption and operationalize AI at scale.

Design, build, and deploy end-to-end data pipelines and ETL/ELT solutions on Databricks. Integrate diverse data sources, implement Spark (PySpark/Scala) transformations, optimize SQL queries, maintain data models, build APIs/data services, ensure data quality/security, monitor/optimize pipeline performance in cloud environments, and follow CI/CD and governance practices.

The role involves acquiring new manufacturing clients, building relationships with IT and data leaders, and identifying business challenges to propose data and AI solutions.

Manage allocation of Databricks consultants across geographies, maintaining high utilization, updating Salesforce and company tools, producing executive reports, and coordinating with Finance, Recruitment, and Delivery while supporting EST and PST time zones.

Develop Generative AI solutions, build predictive models, implement ML pipelines, and collaborate with teams to create scalable AI/ML applications.

The Strategic Alliances Manager will manage relationships with AWS, Microsoft, Google Cloud, and SAP to drive joint GTM initiatives, secure co-investment, and enhance revenue impact through effective partnerships.

The role involves leading ML project implementations, designing production-grade ML solutions, and optimizing AI applications for clients while ensuring effective communication and project management.

The Junior Account Executive focuses on lead generation, relationship management, and executing sales strategies to expand market presence and client partnerships.

As a Data Engineer, you will design and build robust data pipelines, manage data infrastructure, and support data-driven strategies using advanced engineering techniques.

The Full Stack Engineer will develop and maintain web applications using Python. Responsibilities include collaborating on designs, coding, API management, testing, and ensuring code quality.

Designs and architecting data solutions, manages project delivery, ensures alignment with architecture policies, and oversees data accuracy and MDM standards.

In this role, you will lead data engineering strategies, design robust data solutions, mentor engineers, and ensure delivery of scalable infrastructures.

The Technical Project Manager oversees technology projects, managing cloud data engagements, setting timelines, delegating tasks, and ensuring adherence to project metrics. They lead cross-functional teams, monitor progress, and implement risk mitigation strategies, while staying up-to-date with industry trends.

The Senior AI Engineer will lead ML project implementations, manage client engagements, optimize Generative AI and NLP applications, and ensure production-grade ML solutions.