Incedo is a leading US-based consulting firm with over 4,000 employees specializing in data science and technology services. We help clients achieve success through end-to-end digital transformation by combining strong engineering, data science, and design capabilities. We offer a collaborative and fun work environment with ample opportunities for learning and professional growth. Our uniqueness lies in bringing together strong engineering, data science, and design capabilities coupled with deep domain understanding. We combine services and products to maximize business impact for our clients in telecom, financial services, product engineering and life science & healthcare industries.

Working at Incedo will provide you an opportunity to work with industry leading client organizations, deep technology and domain experts, and global teams. Incedo University, our learning platform, provides ample learning opportunities starting with a structured onboarding program and carrying throughout various stages of your career. A variety of fun activities are also an integral part of our friendly work environment. Our flexible career paths allow you to grow into a program manager, a technical architect or a domain expert based on your skills and interests.

As a GenAI Developer at Incedo, you will play a critical role in shaping the future of AI by developing and deploying cutting-edge GenAI applications, specifically focusing on RAG applications. You will leverage your expertise in machine learning, deep learning, generative AI techniques, and software engineering principles to design, implement, optimize, and deploy these applications, ensuring seamless integration with existing workflows and infrastructure.

Role and responsibilities :

- Collaborate with data engineers, data scientists, and stakeholders to understand data requirements, problem statements, and system integrations

- Utilize, apply & enhance GenAI models using state-of-the-art techniques like transformers, GANs, VAEs, and LLM models

- Implement and optimize GenAI models for performance, scalability, and efficiency

- Integrate GenAI models, including LLMs, into production pipelines, applications, and existing analytical solutions

- Develop user-facing interfaces and APIs to interact with GenAI models, including LLMs

- Utilize prompt engineering techniques to enhance model performance, including LLM models

- Apply software engineering principles to develop robust, scalable, and maintainable GenAI applications

- Build and deploy GenAI applications on cloud platforms

- Integrate GenAI applications with other applications, tools, and analytical solutions to create a cohesive user experience and workflow

- Continuously evaluate and improve GenAI models and applications based on data, feedback, and user needs

- Stay up-to-date with the latest advancements in GenAI research, development, software engineering practices, and integration tools

- Document code, models, and processes for future reference

- Build and maintain tools and infrastructure for data processing for AI/ML development initiatives.

Technical skills requirements :

The candidate must demonstrate proficiency in :

- Collaborate with data engineers, data scientists, and stakeholders to understand data requirements, problem statements, system integrations, and RAG application functionalities.

- Use, apply, enhance GenAI models using state-of-the- art techniques like transformers, GANs, VAEs, LLMs (including experience with various LLM architectures and capabilities), and vector representations for efficient data processing.

- Implement and optimize GenAI models for performance, scalability, and efficiency, considering factors like chunking strategies for large datasets and efficient memory management.

- Integrate GenAI models, including LLMs, into production pipelines, applications, existing analytical solutions, and RAG workflows, ensuring seamless data flow and information exchange.

- Develop user-facing interfaces and APIs (RESTful or GraphQL) to interact with GenAI models and RAG applications, providing a user-friendly experience.

- Utilize LangChain and similar tools (e.g., PromptChain) to facilitate efficient data retrieval, processing, and prompt engineering for LLM fine-tuning within RAG applications.

- Apply software engineering principles to develop robust, scalable, maintainable, and production-ready GenAI applications.

- Build and deploy GenAI applications on cloud platforms (AWS, Azure, or GCP), leveraging containerization technologies (Docker, Kubernetes) for efficient resource management.

- Integrate GenAI applications with other applications, tools, and analytical solutions (including dashboards and reporting tools) to create a cohesive user experience and workflow within the RAG ecosystem.

- Continuously evaluate and improve GenAI models and applications based on data, feedback, user needs, and RAG application performance metrics.

- Stay up-to-date with the latest advancements in GenAI research, development, software engineering practices, integration tools, LLM architectures, and RAG functionalities.

- Document code, models, processes, and RAG application design for future reference and knowledge sharing.

Nice-to-have skills :

- Experience working with RAG applications

- Experience with cloud-based data warehousing solutions (e.g., BigQuery, Redshift, Snowflake)

- Experience with cloud-based workflow orchestration tools (e.g., Airflow, Prefect)

- Familiarity with Kubernetes (K8S) is a welcome addition

- Google Cloud certification

- Unix or Shell scripting

Qualifications :

B.Tech., M.Tech. or MCA degree from a reputed university

We are an Equal Opportunity Employer :

We value diversity at Incedo. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.