GenAI Engineer

Luxoft; Gurugram District, Chennai, Bengaluru; Presencial; INR 900.000 - 1.500.000; Tempo integral

Resumo da vaga

Luxoft India is seeking highly skilled Generative AI Engineers to design, develop, and deploy cutting‑edge AI solutions using LLMs, Transformers, and Diffusion models for enterprise clients. You will build chatbots, document QA systems, code assistants, and summarization tools, applying prompt engineering, RAG, vector databases, and scalable AI service architectures.

The role requires 7+ years in AI with 4+ years GenAI, strong Python skills (Java/Node.js also acceptable), and hands‑on experience

Qualificações

• 7+ years in AI with 4+ years GenAI experience.
• Proficient Python; Java/Node.js acceptable.
• Hands-on with LLMs, Transformers, Diffusion models.

Responsabilidades

• Design, prototype, and deploy Generative AI models for enterprise use cases.
• Build and fine-tune LLM-based apps like chatbots, document QA, reports, and code assistants.
• Apply prompt engineering, RAG, and embeddings for accurate results.
• Integrate AI models with enterprise systems and data stores using Python/Java/Node.js.
• Monitor performance, drift, and optimize cost via compression and optimization.
• Collaborate with architects on scalable, secure AI service architectures.

Conhecimentos

Python

Java/Node.js

LLMs

Transformers

Diffusion models

Hugging Face

LangChain

RAG pipelines

Vector databases

Cloud platforms

MLOps

Data engineering

ETL

Formação

Bachelor's/Master's in CS/AI

Ferramentas

MLflow

Kubeflow

Vertex AI

Azure ML

Descrição da vaga

• Project Description:

  We are seeking highly skilled and motivated Generative AI Engineers to join our growing AI team. You will be responsible for designing, developing, and deploying cutting-edge Generative AI solutions using LLMs, Transformers, and Diffusion models. This role involves working on enterprise-grade applications such as intelligent chatbots, document summarization, code assistants, and more.

• Responsibilities:

  Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases.
  Build and fine-tune LLM-based applications such as: Chatbots, Document Q&A systems, Report generators, Code assistants
  and Summarization tools.
  Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance.
  Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js.
  Collaborate with architects to define scalable, secure, and cost-efficient AI service architectures.
  Implement AI/ML pipelines for training, validation, and deployment using tools like MLflow, Vertex AI, or Azure ML.
  Monitor model performance, detect drift, and drive continuous improvement.
  Optimize inference performance and cost through model compression, quantization, and API optimization.
  Ensure compliance with AI ethics, security, and governance standards.
  Prepare and curate training datasets (structured/unstructured text, images, code).
  Apply data preprocessing, tokenization, and embedding generation techniques.
  Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval.
  Partner with business stakeholders to identify and shape impactful AI use cases.
  Contribute to the development of a strategic AI adoption roadmap and reusable AI Workbench/platform components.
  Support POCs, pilots, and full-scale implementations using agile methodologies.
  Document and present solution designs, technical findings, and outcomes to leadership and clients.

• Mandatory Skills Description:

  Overall 7+ years of experience and relevant 4+ years of GenAI.
  Strong programming skills in Python (preferred), with experience in Java or Node.js.
  Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models.
  Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning.
  Familiarity with RAG pipelines, embedding models, and vector databases.
  Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services.
  Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML).
  Strong understanding of data engineering, data pipelines, and ETL workflows.
  Excellent problem-solving, communication, and stakeholder engagement skills.
  Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field.