AI Enterprise Architect

Brickstech; Lahore; On-site; PKR 1,800,000 - 3,200,000; Full time

Job summary

Brickstech is seeking an experienced AI Enterprise Architect who bridges business needs with enterprise technology and AI capabilities.

The role involves engaging with CIOs/CTOs and engineering teams to move rapidly from strategy to execution, architecting enterprise AI platforms, APIs, and integrations while managing risk and scalability.

Qualifications

• 8+ years of software engineering and architecture experience.
• Proven track record delivering enterprise-grade software solutions.
• Experience with APIs, integrations, microservices, and event-driven architectures.
• Strong cloud architecture, security, and performance understanding.
• Real-world AI-powered solution experience with enterprise customers.

Responsibilities

• Translate business requirements into scalable enterprise architectures.
• Lead architecture sessions with CIOs/CTOs and engineering teams.
• Design AI-enabled platforms, integrations, and APIs.
• Define architecture blueprints, roadmaps, and risk controls.
• Evaluate make-vs-buy decisions and ensure security and scalability.

Skills

LLM Applications

Generative AI

AI Agents

RAG

Vector Databases

Embeddings

LLM APIs

AI Orchestration

Model Evaluation

AI Guardrails

AI Observability

Prompt Engineering

Enterprise AI Architecture

Workflow Automation

Multi-Agent Systems

Fine-Tuning

AI Security & Privacy

Tools

AWS

Azure

GCP

Kubernetes

Docker

Terraform

Job description

Job Description

About the Role
We are seeking an experienced AI Enterprise Architect who can bridge business requirements, enterprise technology, software engineering, and emerging AI capabilities.
The ideal candidate has experience in both startup and enterprise environments and understands the balance between rapid execution and scalable architecture. This role requires the ability to engage with CIOs, CTOs, and executive stakeholders while also working closely with engineering teams on architecture, integrations, APIs, and implementation.
This is not a purely advisory or documentation-focused role. We are looking for someone who can move seamlessly from strategy → architecture → execution.

Key Responsibilities

• Solution Architecture
  • Translate business requirements into scalable technical solutions.
  • Design enterprise application, platform, integration, and AI architectures.
  • Define application, data, security, infrastructure, and integration architectures.
  • Create architecture blueprints, specifications, and implementation roadmaps.
  • Evaluate build vs. buy vs. integrate decisions.
  • Identify technical risks, dependencies, and trade-offs.
  • Ensure solutions are secure, scalable, maintainable, and commercially viable.
• Enterprise Architecture & Client Engagement
  • Partner directly with CTOs, CIOs, Heads of Engineering, and Digital Leaders.
  • Lead discovery workshops and architecture sessions.
  • Understand enterprise technology landscapes and integration opportunities.
  • Convert business objectives into actionable technology strategies.
  • Present architecture recommendations to technical and business stakeholders.
  • Support enterprise proposals, POCs, RFPs, and technical evaluations.
• AI & Emerging Technology
  • Architect solutions using LLMs, Generative AI, and AI Agents.
  • Design RAG platforms, knowledge systems, and enterprise AI assistants.
  • Evaluate AI models based on performance, cost, privacy, and latency.
  • Design AI orchestration and multi-agent solutions.
  • Implement vector search, embeddings, and semantic retrieval architectures.
  • Integrate AI solutions with enterprise platforms and APIs.
  • Implement evaluation frameworks, observability, guardrails, and risk controls.
  • Stay current with rapidly evolving AI technologies and architecture patterns.

Startup Environment

We value architects who can:

• Move Fast
• Operate with Ambiguity
• Build MVPs
• Make Pragmatic Decisions
• Work Directly with Founders
• Wear Multiple Hats
• Balance Speed and Scalability

What Success Looks Like

Within the first 90-180 days, you will:

• Establish architecture standards and reusable patterns.
• Lead enterprise architecture discussions and workshops.
• Accelerate solution design and POC delivery.
• Improve enterprise technical credibility.Reduce technical debt while maintaining startup velocity.
• Help productize repeatable enterprise solutions.

Required Experience

• 8+ years of software engineering and architecture experience.
• Experience as a Solution Architect, Enterprise Architect, or Technical Architect.
• Proven track record delivering enterprise-grade software solutions.
• Strong cloud architecture and distributed systems expertise.
• Experience with APIs, integrations, microservices, and event-driven architectures.
• Strong understanding of scalability, reliability, security, and performance.
• Real-world experience architecting AI-powered solutions.
• Experience working directly with enterprise customers and stakeholders.
• Startup or high-growth technology company experience preferred.

AI Experience (Must Have)

• AI Capabilities
  • LLM Applications
  • Generative AI
  • AI Agents
  • Agentic AI
  • RAG
  • Vector Databases
  • Embeddings
  • LLM APIs
  • AI Orchestration
  • Model Evaluation
  • AI Guardrails
  • AI Observability
  • Prompt Engineering
  • Enterprise AI Architecture
  • Workflow Automation
  • Multi-Agent Systems
  • Fine-Tuning
  • AI Security & Privacy

Relevant Technologies

• OpenAI
• Anthropic
• Gemini
• LangChain
• LlamaIndex
• Azure OpenAI
• AWS Bedrock
• Vertex AI
• Pinecone
• Weaviate
• Milvus

Preferred Technical Background

• Architecture
  • Microservices
  • Distributed Systems
  • Event-Driven Architecture
  • Serverless
  • Domain-Driven Design
  • API-First Architecture
• Cloud
  • AWS
  • Azure
  • GCP
  • Kubernetes
  • Docker
  • Terraform
• Backend
  • Python
  • Java
  • Node.js
  • TypeScript
  • .NET
  • REST
  • GraphQL
  • Messaging Systems
• Data
  • PostgreSQL
  • MySQL
  • NoSQL
  • Redis
  • Data Warehouses
  • Vector Databases
  • Data Pipelines
• AI
  • LLM APIs
  • RAG
  • AI Agents
  • Embeddings
  • Vector Search
  • AI Orchestration
  • Model Evaluation
  • AI Observability
• Business & Leadership Skills
  • Understand business problems before proposing technology.
  • Communicate architecture clearly to technical and non-technical audiences.
  • Make ROI-driven decisions.
  • Balance speed, cost, scalability, and technical debt.
  • Influence engineering teams and executive stakeholders.
  • Mentor engineers and architects.
  • Take ownership of technical outcomes.

Key Performance Indicators (KPIs)

• Business
  • Enterprise POC Conversion Rate
  • Technical Contribution to Closed Deals
  • Solution Design Turnaround Time
  • POC Success Rate
  • Customer Technical Satisfaction
• Technology
  • Architecture Quality
  • Scalability
  • Reliability
  • Security Readiness
  • Reusability
  • Technical Debt Reduction
• AI
  • Production AI Solutions Delivered
  • AI Accuracy
  • AI Cost Optimization
  • AI Velocity
  • Reusable AI Components
• Execution
  • Architecture-to-Implementation Cycle Time
  • Engineering Adoption of Standards
  • Successful Roadmap Delivery
  • Reduced Architecture Delivery Blockers