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Gen AI Engineer

Job in Raritan, Somerset County, New Jersey, 08869, USA
Listing for: Arohak Inc.
Full Time position
Listed on 2026-05-31
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Software Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Job Summary

We are seeking a talented Generative AI Engineer to design, develop, and deploy cutting‑edge generative AI solutions. You will work on Large Language Models (LLMs), prompt engineering, and AI‑powered applications to drive innovation and business value.

Key Responsibilities
  • Design and develop generative AI applications using LLMs (GPT, Claude, Gemini, LLaMA).
  • Implement Retrieval‑Augmented Generation (RAG) pipelines for knowledge‑based AI systems.
  • Fine‑tune and optimize LLMs for specific use cases and domains.
  • Build prompt engineering frameworks and templates for consistent AI outputs.
  • Integrate AI models with APIs, databases, and enterprise applications.
  • Develop vector databases and embedding strategies for semantic search.
  • Implement guardrails, security measures, and bias mitigation techniques.
  • Monitor model performance, latency, and cost optimisation.
  • Collaborate with data scientists, ML engineers, and product teams.
  • Stay updated on latest Gen‑AI research, models, and best practices.
Required Skills
  • Strong programming skills in Python.
  • Experience with LLM APIs (OpenAI, Anthropic Claude, Google Gemini).
  • Knowledge of prompt engineering and chain‑of‑thought reasoning.
  • Familiarity with Lang Chain, Llama Index, or similar frameworks.
  • Understanding of RAG architecture and vector databases (Pinecone, Weaviate, Chroma

    DB).
  • Experience with embeddings and semantic search.
  • Knowledge of transformer architecture and attention mechanisms.
  • REST API development and integration.
  • Git version control.
Preferred Skills
  • Experience with fine‑tuning LLMs (LoRA, QLoRA).
  • Knowledge of AI safety, alignment, and responsible AI practices.
  • Cloud platforms (AWS, Azure, Google Cloud Platform) for AI deployment.
  • Docker and Kubernetes for containerization.
  • MLOps and CI/CD pipelines.
  • Experience with agent frameworks (AutoGPT, Lang Graph).
Education

Bachelor's or Master’s in Computer Science, AI/ML, or related field.

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