Gen AI Engineer

1 day ago

Bengaluru, Karnataka, India Thoucentric Full time ₹ 15,00,000 - ₹ 20,00,000 per year

Role & responsibilities

Role Overview

You will be involved in full lifecycle AI solution delivery from research and prototyping to scaling and deployment. The ideal candidate combines strong theoretical ML/DL grounding with applied experience in foundation models, LLM fine-tuning, vector search, Gen AI application frameworks, and deployment on large-scale infrastructure.

Key Responsibilities

  • Architect, build, and deploy Generative AI solutions tailored to business problems.
  • Fine-tune and customize foundation/LLM models (e.g., GPT, LLaMA, Mistral, Falcon, Claude, Gemma).
  • Build LLM-powered applications using frameworks such as LangChain, Haystack, LlamaIndex.
  • Develop and manage RAG (Retrieval Augmented Generation) pipelines integrating vector databases (FAISS, Pinecone, Weaviate, Milvus, ChromaDB).
  • Work with cloud AI services such as Azure OpenAI, AWS Bedrock, SageMaker, GCP Vertex AI.
  • Implement MLOps pipelines for model training/monitoring using tools like MLflow, Kubeflow, Weights & Biases, DVC.
  • Leverage Hugging Face ecosystem (Transformers, Diffusers, PEFT, Datasets) for model experimentation.
  • Optimize AI workflows with GPU acceleration and inference optimization (e.g., ONNX, TensorRT, DeepSpeed, vLLM).
  • Design and enforce secure, ethical, and responsible AI practices in all deployments.
  • Collaborate with consultants, data engineers, and business analysts to understand client problems and deliver measurable solutions.
  • Mentor junior engineers; contribute to internal accelerators and reusable solution templates.

Preferred candidate profile

Required Qualifications

  • Education: Bachelors/Masters in Computer Science, Data Science, AI/ML, or a related field.
  • Experience: 5+ years in ML/DL, with minimum 2 years in Generative AI solution development.
  • Expertise with Python and ML/DL libraries (PyTorch, TensorFlow, JAX).
  • Strong knowledge of LLM training/fine-tuning techniques: LoRA, QLoRA, PEFT, instruction tuning.
  • Proficiency in prompt engineering and evaluation of model outputs.
  • Hands-on with vector databases and indexing pipelines for semantic search.
  • Familiar with containerization and deployment tools (Docker, Kubernetes, Helm).
  • Exposure to CI/CD pipelines for AI solutions and cloud-native patterns.

Preferred Skills

  • Experience in enterprise AI implementation (chatbots, document intelligence, knowledge assistants, customer interaction systems).
  • Exposure to multimodal AI (e.g., CLIP, Stable Diffusion, DALL
    •E, Whisper).
  • Contributions to open-source or personal projects showcasing Gen AI apps.
  • Experience in reinforcement learning (RLHF/DPO) for model alignment.
  • Working knowledge of streaming and event-driven architectures (Kafka, Flink) for real-time AI applications.

What We Offer

  • Opportunity to work on cutting-edge AI projects across industries and domains.
  • Exposure to industry-grade Gen AI stacks from multiple providers.
  • A flat, collaborative environment where innovation and ownership are valued.
  • Competitive compensation and career growth as part of a scaling consulting team.
  • Support for continuous upskilling (certifications, conferences, workshops).

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