Generative Ai Architect

Tredence; Bengaluru; Hybrid; INR 350,000 - 550,000; Full time

Job summary

Tredence seeks a highly experienced Generative AI Architect to lead design, architecture, and solutioning of enterprise-grade GenAI platforms and applications. You will set technical direction, mentor teams, and collaborate with product and data science groups to translate business needs into robust, secure architectures.

This is a hands-on leadership role that combines strategic vision with practical implementation across AWS, Azure or GCP, and modern MLOps pipelines.

Qualifications

• 8–14 years in AI/ML, cloud architecture or enterprise software.
• Hands-on with LLMs and GenAI platforms.
• Experience in RAG, vector DBs and MLOps.

Responsibilities

• Architect end-to-end GenAI solutions across data pipelines and deployment.
• Lead multi-team engineering, governance and roadmap delivery.
• Evaluate models, tuning, grounding, and monitoring.
• Define scalable, secure reference architectures on cloud platforms.

Skills

AI/ML

Cloud architecture

GenAI platforms

LLMs

MLOps/LLMOps

Python

PyTorch

TensorFlow

REST/GraphQL

Docker/Kubernetes

Education

Master's degree in CS/Engineering/AI

Tools

LangChain

LlamaIndex

HuggingFace

Pinecone

FAISS

Weaviate

Job description

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.
• Opportunity to influence AI strategy and enterprise roadmaps.