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Job Description
Structured overview of role & requirementsAbout This Role
Build, deploy, and maintain AI-powered applications and microservices using LLMs and generative AI frameworks to extract insights from complex regulatory and inspection datasets.
Integrate AI capabilities into the Redica platform, including backend APIs and services designed with Python and FastAPI, ensuring scalable AI inference and data processing in production environments.
Collaborate closely with product, data, and software engineering teams to translate product requirements into AI-driven solutions and contribute to testing, monitoring, and performance optimization of AI systems.
Minimum Requirements
3+ years of experience as an ML Engineer with traditional ML models and/or Generative AI applications development and productionization.
Hands-on experience with Python programming and building backend APIs using FastAPI.
Proven expertise working with LLMs and generative AI: experience with third-party LLM APIs (OpenAI, Google, Anthropic, Amazon Bedrock) and open-source LLMs (Llama, Mistral).
Bachelor's degree in Computer Science, Computer Engineering, or a related technical field.
Ideal Candidate Profile
Experienced in building scalable AI services within a microservices architecture, familiar with orchestration and deployment in production environments.
Demonstrated ability to manage complexity across AI models, data pipelines, and distributed services, particularly in handling structured and unstructured regulatory datasets.
Strong integration skills combining AI systems with vector/graph databases and various SQL/NoSQL data stores, enabling hybrid search and large-scale AI inference workflows.