Note: The job is a remote job and is open to candidates in USA. Nexacode is hiring an entry-level AI Engineer to build, test, and improve AI-powered applications using Python, LLMs, and APIs. The role supports development of AI features, prompt and retrieval workflows, output evaluation, responsible AI practices, and collaboration and documentation.
Responsibilities
- Help build and maintain applications that use LLM APIs
- Write Python code to process inputs, call APIs, validate responses, and handle errors
- Assist in creating features such as chat assistants, document Q&A tools, and information extraction workflows
- Develop and test prompts for specific application tasks
- Assist with document processing, embeddings, semantic search, and retrieval-augmented generation (RAG)
- Help improve response quality by testing retrieval results and checking whether answers are supported by source material
- Create test cases and evaluate AI application outputs for accuracy, relevance, and reliability
- Help identify issues such as hallucinations, prompt injection, and exposure of sensitive information
- Document application limitations and escalate unexpected behavior
- Work with software engineers, data teams, and product stakeholders
- Participate in code reviews and team meetings
- Maintain clear documentation for assigned features, tests, and workflows
Skills
- This opportunity is intended for candidates with 0–1 year of full-time professional AI engineering or software development experience
- No prior full-time professional experience is required
- Academic projects, internships, bootcamp projects, personal projects, GitHub portfolios, hackathons, and open-source contributions are valued
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field
- Equivalent practical training and strong project experience may also be considered
- 0–1 year of full-time professional AI engineering or software development experience
- Working knowledge of Python, including functions, data structures, packages, and JSON
- Basic understanding of REST APIs and how applications send and receive data
- Familiarity with LLMs, prompt design, tokens, and common limitations of generated responses
- Introductory knowledge of embeddings, vector search, and RAG
- Familiarity with Git/GitHub and basic testing or debugging practices
- Experience building an AI application or project, whether through coursework, a bootcamp, an internship, or independent work
- Strong problem-solving skills and attention to detail
- Ability to explain technical ideas clearly
- Good communication and collaboration skills
- Curiosity and willingness to learn new tools and techniques
- Exposure to tool calling, AI agents, FastAPI, vector databases, cloud platforms, or application deployment
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