AI Infrastructure Senior Engineer Job in Pakistan (Remote)

A new era of software engineering is beginning in Pakistan. We’re looking for a Senior AI Infrastructure Engineer, not someone who just talks about AI, but someone who actually builds production systems that can automate business operations like support, marketing, and product. 

This role is for engineers who truly understand backend systems, LLM integrations, agentic workflows, and RAG pipelines, and can implement them end-to-end. We’re a fast-growing company focused on AI-driven automation. 

This isn’t about “prompt engineering” or just research; you’ll be doing real engineering where you’ll have to deal with things like hallucinations in models, API failures, and keeping costs in check. If you thrive on shipping and debugging in a fast-paced environment, this is the perfect opportunity.

Salary, Location, and Employment Type

Remote work and international compensation make this a highly attractive role for top engineers in Pakistan:

Location: Remote (Pakistan-based applicants can apply)

Working Hours: 40 hours per week (overlap with PK/Dubai working hours required)

Salary Range: $2,200 – $3,000 USD per month (flexible based on skill and experience)

Employment Type: Full-time Remote

Job Summary and Responsibilities

In this role, you’ll design and maintain the architecture for AI-powered features and internal systems. Your job is to get messy data AI-ready and integrate LLMs into real-world applications.

Key Responsibilities

AI Feature Design: Build AI systems for support automation, marketing workflows, and internal research tools.

LLM Integration: Use hosted APIs like OpenAI, Anthropic, and open-source models like Llama, Mistral, and DeepSeek (via vLLM, Ollama).

Agentic Workflows: Design multi-step LLM pipelines, tool-using agents, and task orchestration.

RAG Systems: Build and maintain end-to-end RAG pipelines (ingestion, chunking, embedding, and vector search).

Data Plumbing: Clean up messy data, call transcripts, and emails, and get them into a structured format so AI can understand them better.

Model Fine-tuning: Where needed, fine-tune small models with LoRA/QLoRA.

Production Reliability: Monitor AI systems, catch regressions, and optimize costs (caching, routing).

Eval Harnesses: Create test sets and scoring rubrics to check AI outputs so there’s no compromise on quality.

Qualifications and Skills

We prefer engineers with strong backend fundamentals who see AI as part of their toolkit.

Backend Engineering: 4+ years of experience building backend services in Python or Node.js.

LLM Production Experience: Practical experience shipping LLMs (hosted or open-source) in real-world systems.

RAG & Vector DB: Knowledge of working with vector databases like Pinecone, Qdrant, or pgvector.

Prompt Design: Ability to create production-level prompts that handle JSON or structured outputs.

Data Handling: Skilled at parsing and cleaning JSON, CSV, and unstructured data (emails, transcripts).

Debugging Mindset: Ability to trace and fix odd AI behavior.

Orchestration Tools: Experience with LangChain, LlamaIndex, n8n, or custom orchestrators.

Role Details

Who Should Apply? (Cultural Fit)

We’re looking for people who care more about real-world AI than its hype. This role is for those who can work independently and adapt quickly to changing priorities. 

We like engineers who understand and validate systems, not just ship “magic boxes.” If you know how to balance the cost, latency, and privacy of models and you don’t shy away from production issues, you belong on our team.

Apply Now

This is a great chance to make a global impact from Pakistan.

Professional Advice

When you apply, make sure your CV highlights AI systems you’ve actually deployed (not just side projects). 

If you’ve fine-tuned open-source models or used any unique approaches to save costs, definitely mention that. We’ll give preference to candidates who can join immediately.