Generative AI Engineer - 4 to 8 Years

Generative Engineer 4 to 8 Years

Experience: 48 Years

Location: Remote

Mode of Engagement: Full-time

No. of Positions: 4

Educational Qualifications: B.E./B.Tech/M.E./M.Tech in Computer Science, AI/ML, Data Science, or related field

Industry: IT AI/ML Services

Notice Period: Immediate

What We Are Looking For

• 48 years of hands-on experience in AI/ML with strong practical exposure toTransformer-based models .
• Proven experience infine-tuning, optimizing, and deploying LLMs (BERT, T5, GPT-style, LLaMA, Mistral, etc.).
• StrongPython skills for model training, inference pipelines, APIs, and system integration.
• Real-world experience working withagentic / multi-agent AI systems (plannerexecutor, supervisorworker patterns, tool-using agents).
• Ability to independently ownmodel development experimentation production deployment .
• Experience handlinglatency, cost, scalability, and monitoring in production AI systems.

Responsibilities

• Design, fine-tune, and deployTransformer-based models for NLP, reasoning, information extraction, and generation tasks.
• Build and managemulti-agent AI systems for task decomposition, orchestration, and decision-making.
• Implementefficient inference pipelines with batching, caching, quantization, and latency optimization.
• Develop production-gradeREST APIs using FastAPI/Flask and containerize services using Docker.
• Collaborate with internal teams and clients to convert business requirements into scalable AI solutions.
• Monitor model performance, accuracy, drift, and cost; continuously improve system reliability.
• Stay up to date with advancements intransformer architectures, LLMs, and agent-based AI systems .

Qualifications

• Bachelors or Masters degree in Computer Science, AI/ML, or a related discipline.
• Minimum4 years of hands-on experience with Transformer architectures.
• Strong working experience withHugging Face Transformers andPyTorch (preferred) or TensorFlow/JAX.
• Solid understanding ofattention mechanisms, encoderdecoder models, embeddings, and fine-tuning strategies .
• Familiarity withmulti-agent frameworks (LangChain, LangGraph, AutoGen, CrewAI, or similar).
• Experience withREST APIs, Docker, Git , and cloud deployment onAWS or GCP .
• Strong communication skills with the ability to explain complex AI concepts to non-technical stakeholders.