AI Engineer (AI-Powered Agents, Knowledge Graphs)

Helpshift - A Keywords Studio, bridges the disconnect between conventional customer service channels such as email and phone support and a growing consumer base that does more on mobile phones and has a strong preference for messaging as the primary mode of communication. Through Helpshift s AI-powered customer service platform, companies can resolve issues more efficiently, boosting customer satisfaction in the process. Companies such as Supercell, Scopely, Rovio, and hundreds of other leading brands use the Helpshift platform to provide messaging-first customer support. Helpshift is installed on two billion devices worldwide and serves more than 820 million active consumers. We are looking for an ambitious, experienced, driven solution orientated individual that thrives in a fast-paced, cutting-edge, technology-driven environment. You will be an integral part of our custom development and professional services team and collaborating with multiple teams to deliver solutions to our clients.

At Helpshift, we have 5 Leadership Principles that we integrate into our every day, and use to guide us in our goals. These principles reflect who we are as part Keywords Studios, and to show who we are when we come together, collectively, with other studios to achieve success:

Title: AI Research Engineer (AI-Powered Agents, Knowledge Graphs)

Location: Pune

Job Type: Full-time

Key Responsibilities:

AI Agent Development: Design, build, and deploy AI-powered agents for applications such as virtual assistants, customer service bots, and task automation systems using LLMs and other AI models.

Knowledge Graph Implementation: Develop and implement knowledge graphs for enterprise data integration, enhancing the retrieval, structuring, and management of large datasets to support decision-making.

AI-Driven Process Optimization: Collaborate with business units to optimize workflows using AI-driven solutions, automating decision-making processes and improving operational efficiency.

Model Monitoring and Maintenance: Establish processes for real-time model monitoring, including tracking performance, drift detection, and accuracy of models in production environments.

Model Retraining and Optimization: Develop automated or semi-automated pipelines for model retraining based on changes in data patterns or model performance. Implement processes to ensure continuous improvement and accuracy of AI solutions.

Cloud and ML Platforms: Utilize platforms such as Azure Machine Learning Studio, Google Vertex AI, AWS Bedrock and open-source frameworks for end-to-end model development, deployment, and monitoring.

Collaboration: Work closely with data scientists, software engineers, and business stakeholders to deploy scalable AI solutions that deliver business impact.

Generative: Should Have a work experience in RAG, Langchain, Llamaindex and generative AI use case implementation and deployment.

Good to have agents framework knowledge or working experience like AutoGen, CrewAI, Langchain-agent, Llamaindex Agent, Swarm by open AI etc.