MetAntz
Company:
https://www.linkedin.com/company/metantz
Seniority: Mid-Senior level
Industries: Technology, Information and Internet
Job details:
Role OverviewWe are looking for a GenAI Developer with strong hands-on experience in building and deploying production-grade Generative AI applications. The ideal candidate should have solid expertise in LLMs, RAG, AI Agents, Python, prompt engineering, and AI application development.Key Responsibilities
- Design, develop, and deploy GenAI-powered applications using LLMs.
- Build and optimize RAG pipelines using enterprise data sources.
- Develop AI Agents and agentic workflows for complex business use cases.
- Work with LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source models.
- Develop and optimize prompts, embeddings, function calling, tool calling, and structured outputs.
- Build semantic search and knowledge-based applications using vector databases.
- Integrate GenAI solutions with REST APIs, microservices, databases, and backend systems.
- Evaluate and optimize LLM applications for accuracy, latency, scalability, reliability, and cost.
- Implement LLM evaluation, monitoring, guardrails, and security for production applications.
- Deploy and scale GenAI applications on AWS, Azure, or GCP.
- Collaborate with Product, Engineering, Data, and Business teams to convert requirements into scalable AI solutions.
- Mentor junior developers, conduct technical reviews, and provide technical guidance to the team.
- Team handling or experience leading a small GenAI/AI engineering team will be an added advantage.Required Skills
- 5–9 years of experience in Software Development, AI/ML, or related fields with strong hands-on GenAI experience.
- Strong programming expertise in Python.
- Hands-on experience building and deploying LLM/GenAI applications.
- Strong understanding of RAG, embeddings, vector databases, and prompt engineering.
- Experience with OpenAI, Azure OpenAI, Anthropic, Gemini, or similar LLM APIs.
- Hands-on experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
- Experience building AI Agents / Agentic AI workflows.
- Strong understanding of REST APIs, microservices, databases, Git, and backend development.
- Experience with at least one cloud platform: AWS, Azure, or GCP.
- Good understanding of LLM evaluation, observability, security, and responsible AI practices.Good to Have
- Experience with LLM fine-tuning, LoRA/PEFT, or open-source models such as Llama, Mistral, or Qwen.
- Experience with MLOps / LLMOps.
- Knowledge of PyTorch or TensorFlow.
- Hands-on experience with Docker and Kubernetes.
- Exposure to CI/CD and cloud-native architectures.
- Experience with multimodal GenAI applications.
- Knowledge of NLP, semantic search, recommendation systems, or document intelligence.
- Prior experience mentoring developers or leading a GenAI/AI engineering team.Soft Skills
- Strong problem-solving and analytical skills.
- Ability to translate business requirements into practical GenAI solutions.
- Strong communication and collaboration skills.
- Ability to independently own projects from POC to production.
- Ability to mentor and guide team members.
- Comfortable working in a fast-paced product environment.EducationBachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, or a related field.
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