AI Architect

2 weeks ago

Ellore, Andhra Pradesh, India beBeeArtificialintelligence Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Job Title: AI Architect - Large Language Model Specialist

As an AI Architect specializing in Large Language Models (LLMs), you will design, develop, and deploy cutting-edge machine learning solutions with a focus on Generative AI. Your role will involve building scalable systems using Python, LLMs, and retrieval pipelines to address complex business challenges and enhance product capabilities.

Key Responsibilities:

  1. Design and implement large-scale ML architectures for Generative AI applications.
  2. Develop and optimize prompt engineering, embeddings, vector databases, and retrieval mechanisms.
  3. Create APIs and services to integrate AI solutions into production environments.
  4. Collaborate with data engineers, product managers, and stakeholders to define technical requirements.
  5. Evaluate and improve model performance and accuracy.
  6. Stay up-to-date with the latest research and developments in GenAI, NLP, and ML.
  7. Contribute to technical documentation, code reviews, and best practices.
  8. Ensure all AI solutions adhere to ethical and data privacy standards.

Required Qualifications & Skills:

  1. Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
  2. Strong programming skills in Python, including use of libraries like TensorFlow, PyTorch, Hugging Face Transformers, LangChain, etc.
  3. Experience with LLMs (GPT, LLaMA, Claude, etc.) and RAG frameworks.
  4. Hands-on experience with vector databases (e.g., FAISS, Pinecone, Weaviate).
  5. Solid understanding of NLP, embeddings, tokenization, and attention mechanisms.
  6. Familiarity with APIs, RESTful services, and cloud deployment (AWS/GCP/Azure).
  7. Strong foundation in data structures, algorithms, and ML workflows.

Soft Skills:

  1. Strong problem-solving and analytical thinking.
  2. Excellent verbal and written communication skills.
  3. Adaptability and willingness to learn emerging technologies.
  4. Collaboration and teamwork in cross-functional environments.
  5. Strong attention to detail and ability to deliver high-quality work.

Preferred Qualifications:

  1. Ph.D. in a relevant field.
  2. Experience deploying LLMs in production environments.
  3. Contributions to open-source GenAI projects or research publications.
  4. Knowledge of MLOps and CI/CD for ML pipelines.
  5. Experience with Kubernetes, Docker, or other containerization tools.

Key Relationships:

  1. AI/ML Team
  2. Data Engineering Team
  3. Product Management
  4. Software Development
  5. IT Security & Compliance
  6. Business Stakeholders

Role Dimensions:

  1. Team Size Managed: None / Optional (if leadership role)
  2. Budget Responsibility: None / Optional
  3. Scope of Impact: Company-wide AI capabilities and customer-facing features
  4. Decision-Making Authority: Technical implementation within AI projects

Success Measures (KPIs):

  1. Time to deploy new ML/GenAI features
  2. Accuracy and performance of deployed models
  3. User engagement and satisfaction with AI features
  4. Uptime and reliability of AI services
  5. Contribution to AI/ML research or innovation within the team
  6. Reusability and scalability of AI code and systems

Competency Framework Alignment:

  1. Technical Expertise: Mastery in Python, ML frameworks, GenAI, and RAG
  2. Innovation: Drives AI innovation and creative problem-solving
  3. Collaboration: Works effectively in multi-disciplinary teams
  4. Execution Excellence: Delivers high-quality, scalable AI solutions
  5. Customer Focus: Builds AI features that enhance user experience
  6. Ethical Responsibility: Ensures responsible AI practices and data governance

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