About the position
Uniphore is one of the largest B2B AI-native companies—decades-proven, built-for-scale and designed for the enterprise. The company drives business outcomes, across multiple industry verticals, and enables the largest global deployments. Uniphore infuses AI into every part of the enterprise that impacts the customer. We deliver the only multimodal architecture centered on customers that combines Generative AI, Knowledge AI, Emotion AI, workflow automation and a co-pilot to guide you. We understand better than anyone how to capture voice, video and text and how to analyze all types of data. As AI becomes more powerful, every part of the enterprise that impacts the customer will be disrupted. We believe the future will run on the connective tissue between people, machines and data: all in the service of creating the most human processes and experiences for customers and employees.
Responsibilities
- Design and implement applications using BigData technologies.
- Design and implement distributed applications using cloud specific services.
- Implement Hybrid cloud approaches to handle data synchronization in between on-premises and on cloud.
- Implement an elastic and serverless platform for data warehousing, which can work seamlessly on different clouds.
Requirements
- 3-5 years of experience in Software Development.
- Strong expertise in Spark, Java/Python, and API code development.
- Strong expertise in database development - Teradata, Oracle.
- Strong problem solving and programming skills.
- Excellent oral and written communication skills.
- Motivated towards working in a startup environment.
Nice-to-haves
- 1+ years working on scalable distributed systems.
- Experience with developing software using a broad range of data source connectors, including JDBC, TPT, RestAPI, Kafka.
- Experience with BigData technologies (one or more of Map-Reduce, Hive, Spark, Sqoop).
- Experience with Cloud Data Warehouses like Snowflake or BigQuery.
- Experience building AI-powered applications using Python.
- Understanding of machine learning lifecycle: data ingestion, training, fine-tuning, evaluation, and deployment.
- Experience with agentic frameworks such as: LangChain, AutoGPT, CrewAI, MetaGPT, LangGraph, or similar.
- Working knowledge of Kubernetes (K8s).
- Hands-on experience or familiarity with cloud platforms such as AWS, Azure, or GCP.
Benefits
- Competitive base pay.
- Annual incentive opportunity based on target achievement.
- Pre-IPO stock options.
- Medical, dental, vision benefits.
- 401(k) with a match.
- Generous paid time off.
- Paid holidays.
- Paid day off for your birthday.
- Other paid leave policies to support employees through all phases of life.
