> Markdown version of [/jobs/ext/4505220-senior-ai-engineer](https://www.wearedevelopers.com/jobs/ext/4505220-senior-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** REDICA Systems - **Location:** Pleasanton, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Cloud Computing, Databases, Computer Engineering, Data Files, Data Stores, Graph Database, Design of User Interfaces, Python (Programming Language), Machine Learning, NoSQL, Open Source Technology, Scrum Methodology, OpenAI, Standard Sql, Azure Machine Learning, Systems Architecture, ReactJS, Large Language Models, Generative AI, Agentic-AI, Fastapi, Kubernetes, Information Technology, Amazon Bedrock, Machine Learning Operations, Streamlit Framework, Microservices - **Published:** November 2, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-ai-engineer-pleasanton-ca--dda75f49-d7e4-4b49-8de4-0b39ca933fcb ## About the Role Artificial Intelligence (AI), Risk, Data Sets, Regulations, International Health, Biology, Vendor/Supplier Management, Biotech and Pharmaceutical, Cloud Computing, Risk Management, * Tech Savvy: Demonstrates expertise in a wide range of technologies and stays ahead of industry trends. * Manages Complexity: Highly experienced in managing complex technical projects and systems. * Plans and Aligns: Proficient in creating comprehensive project plans and ensuring alignment with strategic objectives. * Collaborates: Proactively engages in team projects, contributing ideas and solutions. * Manages Ambiguity: Operates effectively in ambiguous situations and adapts to changing demands. * Engaged: Not only shares our values but also possesses the essential competencies needed to thrive at Redica, as outlined here: https://redica.com/about-us/careers * 5+ years of experience as a senior or lead developer in cloud-based code and system architecture * Deep, hands-on experience in Python * Strong experience in building and deploying LLM and Generative AI applications at scale * Extensive hands-on experience with third-party LLM provider APIs (OpenAI, Google, Anthropic, Amazon Bedrock) and open-source LLMs (Llama, Mistral) * Experience in building conversational systems using LLMs and agentic frameworks * Hands-on experience with microservices architecture and orchestration, including building backend APIs using FastAPI * Experience with vector databases, graph databases, and hybrid (keyword and semantic) search * Hands-on experience working with SQL and NoSQL databases/warehouses * Bachelor''s degree in Computer Science, Computer Engineering, or a related technical field Bonus Points * Familiarity with lightweight UI design using Python/JavaScript frameworks (Streamlit, ReactJS) and integration with ML model backends * Hands-on experience with container orchestration services on AWS (e.g., ECS and EKS) * Experience with both batch and event-driven application architectures and ML inference methods ## Description We're looking for an experienced Senior AI Engineer to join our team as we continue to develop the first-of-its-kind quality and regulatory intelligence (QRI) platform for the life science industry. The ideal candidate will have experience maintaining a high bar of quality while remaining hands-on in the code. Core Responsibilities * Fully understand technical architecture and various ML subsystems * Lead in an Agile Scrum environment with a keen focus on delivering sustainable, high-performance, scalable, and easily maintainable enterprise solutions * Help prioritize technical issues with engineering managers * Proactively guide technical decisions on ML architecture * Ensure successful system delivery to the production environment and assist the operations and support team in resolving production issues as necessary * Develop, test, and maintain architectures for data stores, databases, processing systems, and microservices * Integrate various subsystems or components to deliver end-to-end solutions * Integrate ML services with multiple subsystems