AI Tech Lead

We are looking for an experienced AI Tech Lead to take ownership of our AI engineering direction, solution architecture, technical delivery, and AI-powered product development.

This is a hands-on leadership role for someone who understands both business and technology. You will work closely with the Founder, clients, project managers, developers, and sales team to turn business requirements into scalable AI and software solutions.

The ideal candidate should be comfortable going beyond coding including technical discovery, solution architecture, presales, estimation, team leadership, code reviews, hiring, mentoring, and client-facing technical discussions.

You will be involved in building AI SaaS products, AI agents, automation systems, LLM applications, RAG systems, APIs, data pipelines, and custom software solutions for clients across different industries.

Key Responsibilities1. AI & Technical Leadership

• Define and drive the company's AI technology strategy.
• Design scalable architectures for AI-powered applications and SaaS products.
• Evaluate and recommend AI models, frameworks, APIs, tools, and platforms.
• Lead implementation of LLM, Generative AI, AI Agents, RAG, NLP, and automation solutions.
• Establish technical standards, development practices, and architecture guidelines.
• Ensure solutions are secure, scalable, maintainable, and cost-efficient.
• Stay current with developments in OpenAI, Anthropic, Google, open-source LLMs, AI agents, vector databases, and AI infrastructure.

2. Solution Architecture & Presales

• Participate in client discovery and technical meetings.
• Understand business requirements and translate them into technical solutions.
• Create system architectures, technical approaches, workflows, and solution diagrams.
• Prepare technical proposals, Statements of Work, project estimates, and implementation plans.
• Support the sales team during technical presales calls.
• Conduct technical presentations and product demonstrations.
• Identify technical risks, dependencies, and implementation challenges before projects begin.

3. Team Leadership

• Lead and mentor AI engineers, backend developers, frontend developers, data engineers, and other technical resources.
• Assign technical tasks and establish development priorities.
• Conduct code reviews and architecture reviews.
• Establish engineering best practices.
• Help recruit and interview technical team members.
• Identify skill gaps and create technical development plans for team members.
• Maintain accountability for engineering quality and delivery.

4. Project Delivery

• Work with Project Managers and Business Analysts to translate requirements into technical execution plans.
• Break projects into milestones, modules, APIs, integrations, and development tasks.
• Review project progress from a technical perspective.
• Resolve technical blockers and architectural issues.
• Ensure projects meet agreed technical requirements and quality standards.
• Participate in sprint planning, architecture reviews, demos, and technical retrospectives.

5. AI Engineering

You should be capable of designing and overseeing systems involving:

• LLM applications
• AI Agents
• RAG pipelines
• AI chatbots
• AI voice agents
• AI automation
• Prompt engineering
• Function/tool calling
• Structured outputs
• Multi-agent workflows
• Document intelligence
• Semantic search
• Vector databases
• Embeddings
• Fine-tuning / model customization where appropriate
• AI evaluation and monitoring
• AI-powered SaaS products
• Workflow automation using n8n, Make, or similar platforms

6. Backend & Cloud Architecture

Strong understanding of modern backend and cloud technologies is expected, including:

• Python
• FastAPI / Django / Flask
• Node.js
• REST APIs
• Webhooks
• PostgreSQL / MySQL
• Redis
• Docker
• Git/GitHub
• AWS / Azure / GCP
• CI/CD
• Microservices
• Authentication and authorization
• Third-party API integrations

You don't need to be the strongest programmer on the team, but you must be technically strong enough to review architecture, understand code, troubleshoot complex issues, and guide engineers.

Required QualificationsMust Have

• 6+ years of professional software engineering experience.
• 3+ years of experience working with AI/ML, Generative AI, or LLM-based systems.
• Strong Python experience.
• Strong understanding of software architecture and backend development.
• Hands-on experience building production AI applications.
• Experience with OpenAI or other commercial/open-source LLM APIs.
• Experience with RAG, embeddings, vector databases, and AI agents.
• Experience designing REST APIs and integrations.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience leading or mentoring technical teams.
• Strong Git/GitHub knowledge.
• Strong understanding of databases and system design.
• Excellent communication and problem-solving skills.

Strongly Preferred

• Experience building AI SaaS products.
• Experience with LangChain, LlamaIndex, LangGraph, CrewAI, or equivalent frameworks.
• Experience with n8n, Make, Zapier, or other automation platforms.
• Experience with OpenAI Assistants/Responses APIs or equivalent agent frameworks.
• Experience with voice AI, Twilio, speech-to-text, and text-to-speech.
• Experience with AI evaluation, observability, and monitoring.
• Experience with Docker and Kubernetes.
• Experience with CI/CD and DevOps.
• Experience working directly with international clients.
• Experience in a software agency, consulting company, or startup environment.
• Presales and technical proposal experience.

Leadership Expectations

We are not looking for someone who only manages developers.

The ideal candidate should be able to:

Understand the business → Understand the problem → Design the solution → Estimate the work → Guide the team → Review implementation → Communicate with the client → Deliver the solution.

You should be comfortable moving between:

Client Meeting → Architecture → Proposal → Sprint Planning → Code Review → Troubleshooting → Team Management

AI-First Engineering Environment

We actively use modern AI tools to increase engineering productivity.

You will be expected to explore and implement AI-assisted development workflows using tools such as:

• Cursor
• Claude
• ChatGPT
• GitHub Copilot
• AI coding agents
• n8n
• AI development platforms
• Automated testing and code-review tools

The goal is not simply to use AI tools, but to understand where AI can improve engineering speed, quality, automation, and business outcomes.

What Success Looks Like

Within the first 3–6 months, you should be able to:

• Establish a strong AI engineering architecture and development process.
• Lead multiple AI/software projects simultaneously.
• Improve engineering productivity through AI-assisted development.
• Build reusable AI components and internal frameworks.
• Reduce technical debt and improve code quality.
• Support the sales team with strong technical presales.
• Create accurate technical estimates and solution architectures.
• Build and mentor a high-performing AI engineering team.
• Help the company launch new AI SaaS products.
• Become the primary technical authority for AI-related projects.

Why Join Us?

You'll have the opportunity to:

• Work on real-world AI products and SaaS platforms.
• Work with international clients.
• Lead AI engineering teams.
• Influence our overall technology strategy.
• Work across multiple industries.
• Build AI agents, automation systems, and LLM applications.
• Participate in technical presales and solution architecture.
• Experiment with the latest AI technologies.
• Help build internal AI products from idea to production.

How to Apply

Please send:

• Your CV
• GitHub / portfolio
• LinkedIn profile
• 2–3 AI projects you have personally contributed to
• A brief explanation of the most complex AI system you have designed or built
• Expected salary
• Notice period

We are looking for someone who can think like an architect, execute like an engineer, and lead like a technology owner.

Pay: From Rs400,000.00 per month

Application Question(s):

• Describe the most complex AI system you have personally designed and built.
• If a client asks you to build an AI chatbot that can answer questions from 100,000+ company documents, how would you design the system?
• How would you decide between using an existing LLM API, an open-source model, fine-tuning, or building a traditional ML solution?
• A client wants an AI voice agent that can handle 1,000+ calls per day. How would you architect it?
• Describe a situation where you disagreed with a developer, CTO, founder, or client about a technical decision.
• You inherit an AI project with poor code quality, high API costs, slow response times, and unreliable AI outputs. What would you investigate first?

Work Location: Hybrid remote in Rawalpindi