AI Innovator

2 days ago

Mumbai, Maharashtra, India beBeeGenaiengineer Full time ₹ 1,20,00,000 - ₹ 2,00,00,000

Exciting opportunity to spearhead the development of intelligent AI solutions utilizing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) pipelines, agentic workflows, and edge computing.

Job Description
  • We seek an experienced Generative AI/ML Engineer to design, build, and deploy innovative AI applications leveraging LLMs, RAG pipelines, and edge AI frameworks.
  • The successful candidate will collaborate with cloud-native AI services, LLMOps teams, and enterprise-grade deployment patterns to address complex business challenges.
Key Responsibilities:
  1. Leverage LLMs for Enterprise Applications: Design, develop, and fine-tune LLM-powered applications for various use cases.
  2. Evaluate LLM Performance: Assess the effectiveness of LLM applications and develop observability frameworks.
  3. Implement RAG Pipelines: Utilize vector databases, embeddings, and optimized retrieval strategies to implement RAG pipelines.
  4. Build Agentic Workflows: Develop multi-step reasoning, tool calling, and API integration within agentic AI workflows.
  5. Deploy GenAI Solutions: Integrate GenAI solutions into multi-cloud or hybrid cloud environments.
  6. Optimize Edge AI Deployments: Develop and optimize edge AI deployments for low-latency applications.
  7. Data Strategy and Governance: Create data ingestion, transformation, enrichment, validation, and quality check pipelines for AI preprocessing and governance.
  8. Ai Safety and Compliance: Implement AI safety, bias mitigation, and compliance measures.
  9. Collaborate with LLMOps Teams: Collaborate with LLMOps teams for continuous integration and deployment of AI models.
  10. Benchmark Model Performance: Evaluate model performance, latency, and cost-efficiency.
Required Skills:
  • Proficient in cloud AI services (e.g., AWS Bedrock/SageMaker, Azure AI Foundry, Google Vertex AI).
  • Strong proficiency with Python and LLM frameworks (e.g., PromptFlow, LangGraph, HuggingFace, PyTorch, TensorFlow).
  • Hands-on experience with vector DBs (e.g., Pinecone, Weaviate, Milvus, FAISS, Azure Cognitive Search).
  • Experience building RAG-based and agentic AI solutions.
  • Familiarity with Edge AI frameworks (e.g., NVIDIA Jetson, AWS IoT Greengrass, Azure Percept).
  • Multimodal AI (text, image, speech, video) experience.
  • Strong grasp of APIs, microservices, and event-driven architectures.
  • Knowledge of AI governance (data privacy, model explainability, security).
  • Experience in containerized deployments (Docker, Kubernetes, serverless AI functions).
Preferred Skills:
  • Generative agents with memory and planning capabilities.
  • Real-time AI streaming with WebSockets or Kafka.
  • Prior contributions to open-source GenAI projects.
  • Experience in building, testing, and deploying various ML models.
  • Experience in building MCP, A2A protocol.

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