Senior AI Engineer

EvrenAI; Pakistan; Remote; PKR 4,800,000 - 9,600,000; Full time

Job summary

Evren AI in Pakistan is seeking a Senior AI Engineer to lead the AI architecture and implementation on client engagements, from model selection through production deployment. You will design and build production LLM pipelines, evaluate approaches, mentor engineers, and stay ahead of new models, bringing useful techniques back to the team and shaping projects across the portfolio.

You will collaborate with cross-functional teams to deliver reliable AI solutions at scale, write system specs for

Qualifications

• 5+ years of software engineering with at least 2+ years focused on AI/ML systems in production.
• Deep experience with LLM integration, prompt engineering, RAG, fine-tuning and agent architectures at production scale.
• Strong Python background; familiarity with LLM orchestration frameworks and vector databases.
• You can craft a technical spec a client's CTO can review and approve.
• You have opinions about AI architecture and defend them when challenged.

Responsibilities

• Lead the AI architecture and implementation on client product engagements from model selection through production deployment.
• Design and build production LLM pipelines including RAG architectures, agent systems, and fine-tuning workflows.
• Evaluate and select the right AI approach for each problem, model-agnostic.
• Define AI feasibility, data requirements, and integration strategy before a sprint begins.
• Mentor Full Stack engineers on AI integration best practices.
• Stay ahead of the field with new models, frameworks and techniques and share learnings with the team.
• Contribute to Evren AI's technical thought leadership through blogs, playbooks and open source.

Skills

Python

LLM integration

Production systems

RAG architectures

Education

Bachelor's degree in CS/Software Engineering

Tools

Vector databases

LLM frameworks

Job description

You've moved past proof-of-concepts. You've shipped AI systems in production, dealt with the real problems latency, hallucination, cost, context drift and come out with opinions about how to build reliably. At Evren AI, you'll be the person who defines how intelligence gets built into every product we touch.

What You'll Do

• Lead the AI architecture and implementation on client product engagements from model selection through production deployment
• Design and build production LLM pipelines including RAG architectures, agent systems, and domain-specific fine-tuning workflows
• Evaluate and select the right AI approach for each problem model-agnostic, choosing based on what the product actually needs
• Work in the Discover phase to define AI feasibility, data requirements, and integration strategy before a single sprint begins
• Mentor Full Stack engineers on AI integration best practices
• Stay ahead of the field new models, new frameworks, new techniques and bring what's useful back to the team
• Contribute to Evren AI's technical thought leadership through blog posts, internal playbooks, and open-source contributions

What You Bring

• 5+ years of software engineering with at least 2+ years focused on AI/ML systems in production
• Deep experience with LLM integration prompt engineering, RAG, fine-tuning, agent architectures at production scale
• Strong Python background; familiarity with LLM orchestration frameworks and vector database ecosystems
• The ability to think at the product level a technically correct solution that ships late or confuses the user has failed
• Clear written and verbal communication you can write a technical spec a client's CTO can review and approve
• You have opinions about AI architecture. You can defend them and update them when presented with a better argument.

Bonus If You Have

• Computer vision pipelines
• Predictive analytics & time-series
• Client-facing or consultancy experience
• Published technical writing or open-source
• Data science background

Why This Role

You'll set the AI standard for every product Evren builds. The decisions you make about how intelligence gets architected into a product will shape what clients ship into the world. That's not a small thing.