We are looking for a Senior Backend Engineer with a strong GenAI background to join our team and work 100% dedicated on a strategic project for one of our top clients in the pharmaceutical sector.
In this role, you will design and build advanced backend and AI-driven systems, contributing to the evolution of an enterprise knowledge platform powered by Retrieval-Augmented Generation (RAG) and agentic architectures.
Main Responsibilities
* Design and implement RAG architectures and agentic workflows to improve accuracy, relevance, and performance of AI-powered search and knowledge systems.
* Develop high-quality, modular, and maintainable Python backend services, with a strong focus on testing, type hinting, and clean architecture.
* Build and operate document processing and data pipelines to transform unstructured data into AI-ready formats (e.G. using Airflow, AWS Glue, OCR tools).
* Integrate backend services across complex enterprise systems, including integrations via platforms such as Snaplogic.
* Manage and optimize AWS cloud infrastructure (ECS, EC2, VPC, Lambda) ensuring scalability, security, and cost efficiency.
* Own CI/CD pipelines and containerized workloads using Docker.
* Provide technical leadership to external vendor teams, validating deliverables, guiding architecture decisions, and internalizing platform knowledge.
Requirements
* Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
* 5+ years of experience in backend engineering with ownership of complex systems.
* Advanced software engineering expertise, with a strong focus on modularity, testability, and clean architecture.
* Proven experience designing RAG architectures and agentic workflows.
* Hands-on experience with LLM frameworks (e.G. LangChain, LlamaIndex) and vector databases (Pinecone, Milvus, Chroma or similar).
* Solid experience with AWS cloud infrastructure (ECS, EC2, VPC, Lambda).
* Experience implementing Infrastructure as Code (Terraform, CloudFormation, or AWS CDK).
* High level of autonomy, strong communication skills, and ability to document and explain architectural decisions.
* Fluent English (written and spoken).
Desirable / Nice to Have
* Experience building data engineering pipelines (Apache Airflow, AWS Glue, OCR solutions).
* Familiarity with Snaplogic or similar enterprise integration platforms.
* Exposure to semantic technologies or knowledge graphs (Neo4j, RDF/SPARQL).
* Experience with LLM evaluation and observability tools (Langfuse, Arize, MLflow).
* Experience working in regulated or enterprise environments, ideally within pharma or similar industries.
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