Company Overview:

Jinendra Infotech Pvt Ltd is a technology solutions provider focused on delivering scalable software engineering and digital transformation services. Operating across diverse sectors including finance, retail, and enterprise technology, the company specializes in building robust infrastructure and intelligent systems. With a commitment to technical excellence, Jinendra Infotech supports global clients in modernizing their digital footprint through high-performance engineering and data-driven innovation.

Role Overview:

As a Generative AI Engineer, you will be at the forefront of integrating large language models and generative frameworks into production-grade applications. You will work closely with cross-functional product and data science teams to architect solutions that automate complex workflows and enhance user experiences. This role is pivotal in bridging the gap between experimental AI research and real-world business utility, ensuring that our deployments are not only innovative but also secure, scalable, and highly performant for our end users.

Key Responsibilities:

- Design and implement end-to-end Generative AI pipelines to solve specific business problems and improve operational efficiency for our clients.

- Develop and fine-tune LLM-based applications using Python to ensure high accuracy and relevance in automated content generation and data synthesis.

- Collaborate with engineering teams to integrate AI models into existing software architectures, ensuring seamless performance and low latency.

- Evaluate and optimize model performance through rigorous testing and prompt engineering to meet strict quality benchmarks.

- Maintain documentation and best practices for AI deployment, enabling team-wide knowledge sharing and consistent development standards.

Required Skillset:

- Demonstrated proficiency in Python for building complex data pipelines and backend services.

- Hands-on experience in implementing Generative AI solutions, including working with LLMs, vector databases, and retrieval-augmented generation (RAG) frameworks.

- Strong analytical ability to translate ambiguous business requirements into technical AI specifications.

- Excellent communication skills to articulate technical concepts to non-technical stakeholders and collaborate effectively within a distributed, remote-first environment.

- A background in Computer Science or a related quantitative field, supported by 1 - 10 years of professional experience in software development or AI engineering.

- Proven ability to adapt to evolving AI technologies and frameworks, maintaining a high level of productivity in a fast-paced, multi-location work setup.