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.).
• StrongPythonskills 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 monitoringin production AI systems.

Responsibilities

• Design, fine-tune, and deployTransformer-based modelsfor NLP, reasoning, information extraction, and generation tasks.
• Build and managemulti-agent AI systemsfor task decomposition, orchestration, and decision-making.
• Implementefficient inference pipelineswith batching, caching, quantization, and latency optimization.
• Develop production-gradeREST APIsusing 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 experiencewith Transformer architectures.
• Strong working experience withHugging Face TransformersandPyTorch(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.