What are the responsibilities and job description for the Generative AI Engineer position at Aroha Technologies?
Job Title: Generative AI Engineer
Location: Dallas, TX (Onsite 5 days/week)
Employment Type: Contract
Employment Type: Contract
Role Overview
We are seeking a skilled Generative AI Engineer to design, develop, and deploy enterprise-grade AI solutions using LLMs, RAG pipelines, and agentic AI systems. The ideal candidate will have hands-on experience with modern GenAI frameworks, cloud platforms, and strong software engineering fundamentals.
Key Responsibilities
- Design and develop Generative AI applications using LLMs (OpenAI, Gemini, Claude, Llama, etc.)
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines integrating enterprise data
- Develop AI agents / agentic systems for autonomous workflows and decision-making
- Implement prompt engineering, embeddings, and vector search solutions
- Build scalable APIs and microservices for AI-powered applications
- Integrate AI models with enterprise systems (databases, APIs, data lakes)
- Deploy solutions on AWS / Azure / Google Cloud Platform with CI/CD pipelines
- Implement LLMOps/MLOps practices including monitoring, evaluation, and versioning
- Ensure AI safety, governance, and hallucination mitigation
- Collaborate with stakeholders to translate business requirements into AI solutions
Required Skills
- Strong programming experience in Python (mandatory)
- Hands-on experience with:
- LangChain / LlamaIndex / Agent frameworks
- Vector DBs (Pinecone, FAISS, Weaviate, ChromaDB)
- RAG & embeddings
- Knowledge of LLMs, NLP, and transformer models
- Experience with Docker, APIs, and microservices architecture
- Cloud experience: AWS / Azure / Google Cloud Platform
- Understanding of MLOps / LLMOps (CI/CD, monitoring, evaluation)
Preferred Qualifications
- Experience building production-grade GenAI or agentic systems
- Knowledge of GraphRAG, knowledge graphs, ontology extraction
- Exposure to Databricks / MLflow / Spark
- Experience in fine-tuning LLMs or model optimization
Education
- Bachelor's or Master's degree in Computer Science, AI, ML, or related field
Mandatory / Preferred Certifications (AI-Focused)
Include at least 1 2 of the following:
- Google Cloud Professional Machine Learning Engineer
- Microsoft Azure AI Engineer Associate
- AWS Machine Learning Specialty
- Databricks Generative AI Engineer Certification
- NVIDIA Deep Learning Institute (DLI) Certifications
- OpenAI / LLM / Prompt Engineering certifications (any recognized program)
(Certifications significantly strengthen candidacy for enterprise AI roles.)
Experience
- 5 years in software engineering / AI/ML
- 2 years in Generative AI / LLM-based solutions
Nice to Have
- Experience with agentic AI / multi-agent systems
- Strong understanding of AI governance & responsible AI
- Prior experience working in onsite enterprise environments