AI Native Software Engineer - LLM/Generative AI

Role Overview :

As an AI Native Software Engineer, you will be at the forefront of designing and deploying intelligent systems that redefine how businesses interact with data. You will work closely with cross-functional product teams, data scientists, and stakeholders to architect end-to-end AI solutions that are not just experimental, but production-ready.

Your day-to-day will involve building sophisticated LLM-driven applications, optimizing model performance, and integrating agentic workflows into existing microservices architectures. This role is pivotal in driving the company's AI roadmap, ensuring that our technical output directly translates into measurable efficiency and innovation for our clients.

Key Responsibilities :

- Architect and implement scalable AI-native applications using Generative AI and LLM frameworks to solve complex enterprise-level business problems.

- Develop and maintain agentic AI workflows and autonomous systems that automate intricate decision-making processes for internal and external stakeholders.

- Design robust RAG (Retrieval-Augmented Generation) pipelines to enhance the accuracy and contextual relevance of AI-generated outputs.

- Build and manage high-performance microservices that integrate seamlessly with cloud-native environments to ensure system reliability and low latency.

- Optimize prompt engineering strategies and model fine-tuning processes to maximize the utility and cost-efficiency of deployed AI models.

- Collaborate with engineering teams to establish best practices for AI deployment, monitoring, and lifecycle management in production environments.

- Translate high-level business requirements into technical AI architectures that are modular, maintainable, and scalable.

Required Skillset :

- Demonstrated expertise in building AI-native applications using Python, with a deep understanding of modern frameworks like PyTorch and TensorFlow.

- Proven ability to design and implement RAG architectures and utilize VectorDBs to manage large-scale unstructured data effectively.

- Strong experience in orchestrating complex AI workflows using LangChain and other agentic AI frameworks to deliver intelligent software solutions.

- Proficiency in designing microservices-based architectures that are cloud-native, ensuring high availability and seamless integration with existing enterprise stacks.

- Exceptional problem-solving skills with the ability to navigate ambiguity and communicate complex technical concepts to non-technical stakeholders.

- A minimum of 6 to 10 years of professional experience in software engineering, with a specific focus on Machine Learning and Deep Learning applications.

- Ability to thrive in a distributed work environment, maintaining high levels of productivity and collaboration across multiple locations including Bhopal, Hyderabad, Jaipur, Gurgaon, and Pune.

- Strong academic background in Computer Science, Engineering, or a related quantitative field, complemented by a track record of continuous learning in the rapidly evolving AI landscape.

(ref:hirist.tech)