We are seeking a highly experienced Generative AI Architect to lead the design, architecture, and solutioning of enterprise-grade GenAI platforms and applications. The ideal candidate will have deep expertise in AI/ML, LLMs, prompt engineering, vector databases, and cloud-native architectures, with proven experience delivering scalable AI solutions across complex environments.

Key Responsibilities

1. Architecture & Solution Design

- Architect end-to-end GenAI solutions, including data pipelines, model selection, LLM fine-tuning, RAG frameworks, orchestration, and deployment.
- Design scalable, secure, and cost-optimized GenAI reference architectures on Azure/AWS/GCP.
- Define solution blueprints integrating LLMs, vector DBs, data lakes, enterprise APIs, and microservices.
- Evaluate and select appropriate foundation models (OpenAI, Anthropic, Meta, Google, etc.) based on business needs.

2. Technical Leadership

- Provide architectural governance and best practices across multiple GenAI initiatives.
- Guide engineering teams on model integration, optimization, evaluation, and MLOps/LLMOps.
- Drive PoCs, feasibility studies, and technology assessments.

3. RAG & LLM Engineering

- Architect Retrieval-Augmented Generation (RAG) systems using vector stores (Pinecone, FAISS, Weaviate, etc.).
- Optimize prompt engineering, model evaluation, grounding, hallucination reduction, and response accuracy.
- Implement model fine-tuning, domain adaptation, and performance monitoring.

4. Data Engineering & Security

- Design data ingestion, governance, and preprocessing pipelines for structured, unstructured, and multimodal data.
- Ensure compliance with enterprise security, privacy, model safety, and responsible AI frameworks.
- Collaborate with data engineering teams to integrate with enterprise data platforms.

5.



Stakeholder Engagement & Delivery

- Work with business leaders to identify GenAI use cases, define roadmaps, and build ROI-driven solutions.
- Prepare and deliver solution proposals, architecture documents, technical presentations, and cost estimates.
- Collaborate with product, engineering, data science, and cloud teams for end-to-end delivery.

Required Skills & Experience

Core Technical Skills

- 8-14 years of experience in AI/ML, cloud architecture, or enterprise software engineering.
- 35+ years hands-on experience in LLMs / GenAI platforms.

- Strong expertise in
- LLMs (OpenAI, GPT, Claude, Gemini, Llama, etc.)
- GenAI frameworks: LangChain, LlamaIndex, HuggingFace
- RAG architecture, vector databases, embeddings
- Cloud platforms: AWS (Bedrock/SageMaker), Azure (OpenAI/ML), GCP (Vertex AI)
- Python, PyTorch, TensorFlow, REST, GraphQL
- CI/CD, MLOps/LLMOps, containerization (Docker, Kubernetes)

Architecture & Solutioning Skills

- Enterprise architecture (TOGAF is a plus).
- Building scalable, distributed microservices.
- Design of secure AI systems with RBAC, encryption, data masking, model governance.

Soft Skills

- Strong communication and executive-level presentation skills.
- Ability to translate complex technical concepts into business-friendly language.
- Proven leadership in multi-functional teams.

Preferred Qualifications

- Master’s degree in Computer Science, Engineering, AI/ML, or related field.
- Certification in cloud architecture (AWS/Azure/GCP).
- Experience in multimodal AI, agents, or advanced model fine-tuning.
- Prior experience as an AI architect or lead ML engineer.

Why Join Us

- Lead strategic AI transformation initiatives for global clients.
- Work with cutting-edge GenAI tools, models, and frameworks.
- Chance to influence AI strategy and enterprise roadmaps.

📌 Generative Ai Architect (Bengaluru)
🏢 Tredence
📍 Bengaluru