Building modern AI applications at Seismic

I am hiring to build a world class product engineering team at Seismic Inc. for our Hyderabad (India) location! Seismic (Seismic.com) is the global leader in enablement, empowering organizations to engage customers, enable teams, and ignite revenue growth. At the forefront of innovation, Seismic leverages artificial intelligence to enhance sales and marketing effectiveness. Their AI-powered solutions provide go-to-market teams with insights and recommendations, enabling sellers at leading enterprises in a variety of verticals such as Financial Services and Technology to deliver personalized buyer experiences and drive revenue growth.

We believe the evolution of current generation of foundational language models in AI is truly exciting for application builders and are therefore looking to leverage talent in India to build a first class AI products team with data scientists, platform engineers and front end engineers. Our modern software stack is fully microservices based delivering containerized apps for multi-cloud deployment built using React/React native, .Net, Kafka, Postgres, MongoDB, Elastic and Snowflake.

Please read below to get more details on how we are using AI and the challenges we see that keep us excited.

Seismic’s approach to deploying AI applications is grounded in a robust multi-cloud strategy, which leverages Large Language Models (LLMs) from top-tier providers such as Microsoft Azure, IBM, and Google. This design not only provides enhanced flexibility and scalability but also improves system resilience and mitigates risks like vendor lock-in or localized service outages. From a technical standpoint, this requires sophisticated orchestration layers that can dynamically distribute workloads and balance performance across disparate cloud environments.

The AI-powered enablement tool, Aura Copilot, is a prime example of how Seismic harnesses these advanced technologies. Leveraging the natural language generation (NLG) capabilities of LLMs, Aura Copilot can assist in drafting sales materials and provide instant, contextually relevant responses for human training and feedback use cases. However, using these models effectively to align with domain-specific language while ensuring consistency in tone and quality presents a significant technical challenge, requiring measures like continuous model evaluation. When combined with the need for strict compliance with GDPR and Financial Services regulations such as FINRA, this becomes an even more complex and exciting problem.

Developing such an AI-driven application involves addressing several complex challenges:

? Model Integration and Interoperability: Combining LLMs from multiple cloud providers requires ensuring interoperability, managing differing API standards, and aligning performance metrics across platforms.

? Data Security and Compliance: In a multi-cloud environment, safeguarding sensitive business data is paramount. This involves implementing robust encryption protocols, access controls, and compliance with regulations such as GDPR or HIPAA.

? Latency and Scalability: Handling high volumes of requests in real-time necessitates efficient load balancing and low-latency inference mechanisms. Techniques such as model caching, asynchronous processing, and distributed computing are often employed to meet these demands.

By addressing these technical and operational challenges, we are able to deploy Aura Copilot as an enterprise-grade tool that not only enhances sales and marketing effectiveness but also drives revenue growth and improves customer engagement. With several large customers in production and rapidly expanding the use of Aura Copilot, we are seeing a significant momentum in the business.

Aura Copilot is just the start! We have a whole pipeline of SaaS products to build across the entire chain of use cases that we believe will empower the sales teams with next generation intelligent solutions that drive business growth.

Come join us!

?