Generative AI Developer / Engineer / Analyst

New

JobgetherGenerative AI

Based in India; Fully remote working opportunity based in Karnataka, India.Full-TimeMiddle

Salary not disclosed

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Job Details

Languages: Strong written English skills
Experience: 2–3 years of hands-on experience developing Generative AI or LLM-based applications; 1–3 years of practical experience designing, testing, and optimizing prompts; 2–3 years of experience in data analysis, business analysis, or analytics-focused roles.
Required Skills: PythonData AnalysisReactRESTful APIsPrompt EngineeringGenerative AI

Have 2–3 years of hands-on experience developing Generative AI or LLM-based applications.
Have 1–3 years of practical experience designing, testing, and optimizing prompts.
Have 2–3 years of experience in data analysis, business analysis, or analytics-focused roles.
Be proficient in at least one modern programming language, such as Python, Java, Node.js, or .NET.
Have demonstrated experience building complete applications, not only standalone models, prototypes, or scripts.
Have practical experience with internal, private, or enterprise LLM platforms.
Understand RAG architectures, vector databases, and semantic search.
Have experience with REST APIs, backend services, and service-oriented application architectures.
Be familiar with modern frontend frameworks such as React, Angular, or Vue.
Understand LLM limitations, including hallucinations, bias, and model drift, and methods for validating and evaluating outputs.
Understand trade-offs among AI application costs, response latency, scalability, and performance.
Have strong written English skills for prompt development, technical documentation, and communicating AI behavior.
Nice to have: experience with Blue Prism or other RPA platforms, enterprise web applications, LLMOps or MLOps, document-intensive environments, or regulated industries.

Design, build, and optimize end-to-end applications using internal and private Large Language Model platforms.
Create, test, refine, and maintain prompts for accurate and contextually relevant outputs.
Implement few-shot prompting, prompt chaining, and Retrieval-Augmented Generation.
Establish prompt testing, evaluation, documentation, and version-control practices.
Develop backend services, APIs, and web interfaces that integrate AI into existing systems and workflows.
Connect LLMs with enterprise applications, databases, and internal platforms through REST APIs and service-oriented architectures.
Analyze, validate, and transform structured and unstructured data for AI-powered workflows.
Work with business stakeholders to translate operational challenges into LLM-driven solutions.
Collaborate with automation teams to identify opportunities to integrate Generative AI into existing processes.
Document application architecture, prompt strategies, design decisions, and system behavior, while following enterprise security, privacy, compliance, and governance standards.

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