Location: Pune India (Hybrid)
Company: Avegen Health
Type: Full-time
About the Role
Avegen is building next-generation AI-powered solutions to enhance workflows across the pharmaceutical value chain. We are looking for an Applied AI Engineer who can leverage modern AI technologies (including LLMs and automation frameworks) to design, build, and
deploy real-world solutions. This role is ideal for an engineer who combines strong software development skills with practical AI application experience, and can translate business problems into scalable AI-driven systems. You will work closely with domain experts and stakeholders to develop intelligent applications that improve research, regulatory, and commercial operations. As an early member of this initiative, you will help shape the technical direction, prototype solutions, and contribute to production-ready systems.
Key Responsibilities
• Design and build AI-powered applications and workflows to solve real-world business
problems
• Develop systems that integrate large language models (LLMs) with APIs, databases,
and enterprise tools
• Build and deploy end-to-end AI solutions, from prototyping to production
• Implement retrieval-augmented generation (RAG) pipelines for document
intelligence and knowledge workflows
• Develop intelligent services for data retrieval, analysis, and automated insights
generation
• Integrate AI capabilities into existing or new software platforms and backend systems
• Collaborate with business and domain teams to translate requirements into scalable
technical solutions
• Optimize solutions for performance, reliability, and cost efficiency
• Deploy and maintain applications in cloud environments (AWS, Azure, or GCP)
Required Skills & Experience
• 2–5 years of experience in software engineering or backend development
• Strong proficiency in Python and building APIs/services (FastAPI, Flask, etc.)
• Hands-on experience building AI-enabled applications using LLMs (OpenAI,
Anthropic, or similar)
• Experience in developing end-to-end AI/ML or GenAI-based solutions
• Practical knowledge of RAG, embeddings, and vector databases
• Experience integrating APIs, data sources, and third-party services
