Artificial Intelligence Architect

Intellect Design Arena; Chennai District; On-site; INR 6,000,000 - 9,000,000; Full time

Job summary

Intellect Design Arena is seeking an experienced AI Architect to lead enterprise-scale GenAI solutions. You will bridge cutting-edge GenAI with robust engineering architectures to deliver scalable, secure, production-ready AI systems.

The role requires twelve-plus years in software/data engineering with 4+ years in AI/ML architecture, deep cloud and MLOps expertise, and strong communication with both technical and executive stakeholders. Chennai-based, on-site roles.

Qualifications

• Twelve plus years in software/data engineering with at least 4+ years in AI/ML architecture roles.
• Hands‑on experience building production systems with LLMs (GPT, Claude, Gemini, Llama, Mistral, etc), RAG architectures, vector stores, and agentic frameworks.
• Deep knowledge of distributed systems, cloud platforms (AWS/Azure/GCP), containerization (Kubernetes, Docker), and CI/CD for ML (MLOps/LLMOps).
• Proficiency in Python; working knowledge of Java, Go, or TypeScript is a plus.
• System design capable of scale, fault tolerance, and low-latency inference.
• Excellent communication to explain complex tech to engineers and executives.

Responsibilities

• Define end-to-end GenAI architecture for enterprise solutions including LLM-powered apps, RAG pipelines, and multi-model orchestration.
• Evaluate, select, and integrate foundation models based on cost, latency, accuracy, and compliance.
• Design prompt frameworks, guardrails, and evaluation strategies for GenAI systems.
• Architect fine-tuning, distillation, and model customization pipelines as needed.
• Stay current with GenAI advancements and translate research into practical enterprise use.

Skills

GenAI Architecture

Engineering Architecture

Data & ML Platforms

Programming Python

System Design

Communication

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Haystack

Pinecone

Weaviate

Qdrant

pgvector

SageMaker

Vertex AI

Kubeflow

Weights & Biases

Job description

AI Architect

Role Title

AI Architect

Experience Level

Twelve Plus Years Overall (Four Plus Years in AI/ML Architecture)

Core Focus

GenAI Architecture & Strategy, Engineering Architecture, MLOps/LLMOps, Customer Engagement, Governance

Role Overview

We are looking for an experienced AI Architect to lead the design and implementation of enterprise-scale AI/GenAI solutions. This role bridges the gap between cutting-edge generative AI capabilities and robust engineering architectures, ensuring our AI systems are scalable, secure, and production-ready.

Key Responsibilities

GenAI Architecture & Strategy

• Define and own the end-to-end architecture for Generative AI solutions including LLM-powered applications, RAG pipelines, agentic workflows, and multi-model orchestration.
• Evaluate, select, and integrate foundation models (commercial and open-source) based on cost, latency, accuracy, and compliance requirements.
• Design prompt engineering frameworks, guardrails, and evaluation strategies for GenAI systems.
• Architect fine-tuning, distillation, and model customization pipelines where needed.
• Stay current with the rapidly evolving GenAI landscape and translate research advancements into practical enterprise solutions.

Engineering Architecture

• Design scalable, resilient, and cost-efficient cloud-native architectures for AI/ML workloads.
• Define reference architectures, design patterns, and technical standards for AI system development across the organization.
• Architect data pipelines, feature stores, vector databases, and model serving infrastructure.
• Ensure non-functional requirements performance, security, observability, disaster recovery — are built into every solution.
• Drive API design, microservices decomposition, and integration patterns for AI-enabled products.

Customer Engagement & Consulting

• Serve as the primary technical advisor for enterprise clients, leading discovery workshops, solution briefings, and architecture deep-dives.
• Translate client business challenges into well-scoped AI/GenAI solution architectures, producing proposals, statements of work, and technical roadmaps.
• Drive pre-sales and proof-of-concept engagements, demonstrating solution value and accelerating client decision-making.
• Gather and synthesize customer feedback to influence product direction and shape reusable consulting accelerators.
• Represent the organization at client executive briefings, industry conferences, and external AI forums.

Leadership & Governance

• Collaborate with product, engineering, data science, and platform teams to align AI architecture with business goals.
• Establish AI governance frameworks covering model lifecycle management, bias/fairness monitoring, and responsible AI practices.
• Conduct architecture reviews, provide technical mentorship, and build internal capability in AI/GenAI.
• Create and maintain architecture decision records (ADRs), technical documentation, and roadmaps.
• Represent the organization in vendor evaluations, technology partnerships, and industry forums.

Required Qualifications & Skills

• Experience: Twelve plus years in software/data engineering with at least 4+ years in AI/ML architecture roles.
• GenAI Expertise: Hands‑on experience building production systems with LLMs (GPT, Claude, Gemini, Llama, Mistral, etc), RAG architectures, vector stores (Pinecone, Weaviate, pg vector), and agentic frameworks (LangChain, LangGraph, CrewAI, or similar).
• Engineering Architecture: Deep knowledge of distributed systems, cloud platforms (AWS/Azure/GCP), containerization (Kubernetes, Docker), and CI/CD for ML (MLOps/LLMOps).
• Data & ML Platforms: Experience with ML platforms (SageMaker, Vertex AI, Databricks), data orchestration (Airflow, Dagster), and streaming systems (Kafka, Flink).
• Programming: Strong proficiency in Python; working knowledge of Java, Go, or TypeScript is a plus.
• System Design: Proven ability to design systems that handle scale, fault tolerance, and low‑latency inference.
• Communication: Ability to articulate complex technical concepts to both engineering teams and executive stakeholders.

Preferred Qualifications

• Experience with multi-modal AI systems (text, image, audio, video).
• Familiarity with AI safety, alignment, and responsible AI frameworks.
• Exposure to edge/on-device AI deployment.
• Contributions to open-source AI projects or published research.
• Experience in regulated industries (finance, healthcare, government) with compliance-aware AI deployments.

Indicative Tech Stack

Area

Technologies

Foundation Models

• OpenAI GPT, Anthropic Claude, Google Gemini, Meta Llama, Mistral

GenAI Tooling

• LangChain, LangGraph, LlamaIndex, Semantic Kernel, Haystack

Vector Databases

• Pinecone, Weaviate, Qdrant, pgvector, ChromaDB

ML/MLOps

• SageMaker, Vertex AI, MLflow, Kubeflow, Weights & Biases

Cloud & Infra

• AWS / Azure / GCP, Kubernetes, Terraform, Docker

Data

• Spark, Kafka, Airflow, Snowflake, Delta Lake

Observability

• Datadog, Grafana, LangSmith, Arize AI

What You'll Influence

• The GenAI strategy and technical direction of the organization.
• Build vs. buy decisions for AI capabilities.
• Engineering culture around AI-first product development.
• Talent development and hiring standards for AI engineering teams.

We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.