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Job Description & How to Apply Below
Experience- 3-5
Years
Location
- Bangalore/Delhi (Hybrid)
About the Role
Elucidata is seeking a motivated GenAI Engineer to join our Delivery team. In this customer-facing role, you will bridge the gap between cutting-edge Generative AI technologies and real-world life sciences challenges. You will work closely with pharmaceutical and biotech clients to architect and deploy custom AI solutions on top of our Polly platform, ensuring they derive actionable insights from their biomedical data.
You will be instrumental in building and optimizing complex AI systems, moving beyond simple RAG pipelines to design sophisticated Agentic Orchestration frameworks. Your work will involve fine-tuning LLMs for domain-specific tasks and developing scalable cloud architectures.
This role offers a unique opportunity to apply engineering rigor to biological problems, working alongside a multi-disciplinary team of scientists and engineers to deliver high-value solutions to our partners.
What You’ll Own
Design, develop, and deploy production-grade Generative AI solutions, focusing on Agentic Orchestration and RAG pipelines tailored to specific customer needs in the Life Sciences domain.
Collaborate with the Delivery and Commercial teams to understand client requirements and translate them into technical specifications and scalable architectures.
Implement and optimize workflows using Python and LLM frameworks (e.g., Lang Chain, Llama Index, Auto Gen) to extract structured insights from unstructured biomedical data.
Conduct in-depth LLM workflow optimization to improve latency, cost-efficiency, and response accuracy in production environments.
Work with cloud infrastructure (AWS) to ensure the security, scalability, and performance of delivered AI solutions.
Fine-tune and evaluate Large Language Models (LLMs) on domain-specific datasets to improve performance on tasks like metadata curation and entity extraction.
Synthesize feedback from client deployments to collaborate with the Product team on platform enhancements.
Maintain rigorous documentation and code quality standards to ensure seamless handover and long-term maintainability of client projects.
What Makes You a Great Fit
Strong proficiency in Python and software engineering best practices (version control, testing, CI/CD).
Hands-on experience building applications with LLMs, with a specific focus on Agentic Orchestration , RAG, and vector databases (e.g., Pinecone, Milvus).
Experience with LLM workflow optimization , prompt engineering, and debugging complex data pipelines.
Experience with cloud platforms, preferably AWS, and containerization tools like Docker.
An analytical mindset with the ability to solve complex technical challenges.
Excellent communication skills, with the ability to explain technical AI concepts to non-technical stakeholders or domain scientists.
Experience in a customer-facing or solution delivery role is highly desirable.
Prior domain knowledge in Life Sciences, Biology, or Pharma is a significant plus.
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