AI Engineer

Ovii's Interpretation of the Role

We are hiring an AI Engineer to design, develop, and deploy generative AI and large‑language‑model solutions for gaming products. The role builds autonomous AI agents, creates production‑grade pipelines, and partners with data engineers to deliver scalable, high‑performance models.

Role Snapshot

• Design & deploy generative AI models
• Build autonomous LLM‑driven agents
• Create production‑grade AI pipelines
• Collaborate with data engineering
• Optimize model performance
• Stay current with GenAI advances

Must-Have Requirements

• Python
• LLM libraries (Transformers, vLLM, Accelerate, PEFT/LoRA, DSPy)
• FastAPI or Flask
• LangChain or LlamaIndex
• AI agentic frameworks (LangGraph, AutoGen, CrewAI)
• Vector databases & RAG pipelines
• TensorFlow or PyTorch
• AWS, Azure, or GCP
• ML/AI model development
• Large Language Model implementation
• Production deployment of AI solutions
• Bachelor's, Master's, or PhD in Computer Science, Data Science, or related field

Nice-to-Have Signals

• Advanced prompt engineering techniques
• Fine‑tuning LLMs for domain‑specific tasks
• Multimodal learning (vision + language)
• LLMOps/MLOps practices (containerization, CI/CD)
• Publications or open‑source contributions
• Prompt engineering
• Multimodal learning
• LLMOps/MLOps practices
• Open‑source AI contributions

Work Setup

• Location: India
• Work mode: REMOTE
• Remote scope: COUNTRY_RESTRICTED
• Remote countries: India
• Employment type: Full-Time

Not Specified in JD

• Visa sponsorship
• Salary range
• Notice period
• Travel requirements

What You'll Likely Work On

• Design and implement generative AI and conversational LLM solutions for gaming applications
• Develop autonomous AI agents using frameworks such as LangChain, LangGraph, and CrewAI to automate complex business logic
• Build and maintain scalable AI pipelines and RESTful APIs (FastAPI/Flask) for model deployment
• Collaborate with data engineers to curate and preprocess large datasets for training and evaluation
• Fine‑tune and optimize foundation models (e.g., Gemini, GPT‑4, Claude) for production performance
• Monitor and improve model latency, accuracy, and cost to meet business requirements
• Research emerging GenAI technologies and propose innovative enhancements

Good Fit If You Have

• Experience with advanced prompt‑engineering techniques
• Familiarity with multimodal AI (vision‑language) models
• Publications or open‑source contributions in modern AI domains
• Knowledge of LLMOps/MLOps practices, including containerization and CI/CD pipelines