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Known employer, metro location, generalist backend role, and broad cloud/GenAI skillset increase applicant competition.
Core backend, cloud, and GenAI skills transfer across industries, though manufacturing IT ops domain adds moderate specialization.
Specific mandatory tech stack (Python, FastAPI, LLM/vector DB, AWS) creates moderate filtering beyond generic requirements.
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Design, build, and maintain scalable RESTful APIs using Python and FastAPI, integrating Large Language Models (LLMs), vector databases, and prompt engineering techniques for AI-driven IT operations solutions in manufacturing.
Deploy and manage backend services on AWS using Lambda, ECS, API Gateway, with a focus on performance, scalability, and security best practices.
Collaborate with cross-functional teams including product, frontend, and DevOps to translate business requirements into cohesive, high-quality AI backend solutions.
Proficiency in backend development with Python and FastAPI, RESTful APIs, microservices, and security best practices.
Hands-on experience with SQL/NoSQL databases and AWS cloud services including Lambda, ECS, API Gateway, S3, RDS/DynamoDB.
Familiarity with Generative AI concepts including embeddings, vector search, LLM integration (e.g., OpenAI API), and prompt engineering techniques.
Qualifications: Bachelor’s degree in Computer Engineering, Computer Science, Information Technology, or Master’s in Software Engineering; Work Experience Required: Not explicitly mentioned in the JD.
Engineer with demonstrated experience at the intersection of backend engineering and AI/Generative AI technologies, particularly integrating LLMs and vector databases.
Practitioner comfortable with cloud-native deployment and CI/CD pipelines, optimizing backend systems for cost, performance, and reliability on AWS.
Collaborator able to work closely with product management and multiple technical teams in an agile environment to deliver advanced AI-powered features catering to manufacturing IT operations.