AI Engineer | Pakistan

Volga Partners; Islamabad; Hybrid; PKR 1,674,000 - 4,464,000; Full time

Benefits offered by this job

Medical insurance

PTO

Holiday pay

Career development

Job summary

Volga Partners in Islamabad is seeking an AI Engineer to design, deploy, and scale advanced AI systems, including LLMs, RAG frameworks, agentic workflows, and intelligent automation solutions. You will work closely with software engineers, product teams, and leadership to deliver AI-powered capabilities for global clients.

The role emphasizes hands-on model training, evaluation, and production-ready implementations, with a hybrid work arrangement (3 days in office, 2 days remote) and a 90‑day

Responsibilities

• Design, build, and deploy AI systems, including LLMs, RAG, agentic workflows, and ML/DL solutions.
• Train and fine‑tune models using PyTorch or Keras, including data preparation and evaluation.
• Build APIs, inference pipelines, and backend integrations.
• Own evaluation metrics and track quality, latency, and cost.
• Monitor, debug, and optimize AI systems post‑launch.
• Collaborate with software engineers and product teams to integrate AI into applications.
• Document architecture, implementation approaches, and key technical decisions.
• Read and evaluate ML research papers and translate ideas into working code.

Job description

Department: Engineering
Reports To: Product & Engineering Leadership
Location: Islamabad, Pakistan
Office Arrangement: Hybrid – 3 days in office, 2 days remote
Working Hours: 07:00 PM – 04:00 AM PKT
Monthly Salary: PKR 150,000 – PKR 400,000, commensurate with experience and expertise

Position Overview

The AI Engineer at Volga Partners will design, develop, and deploy advanced AI systems, including LLMs, RAG frameworks, agentic workflows, and intelligent automation solutions.

This role requires strong research-to-production skills, hands‑on model training experience, and the ability to integrate AI into real‑world applications.

The AI Engineer will work closely with software engineers, product teams, and leadership to deliver scalable AI-powered solutions for global clients.

Key Responsibilities

• Design, build, and deploy AI systems, including LLMs, RAG, agentic workflows, and ML/DL solutions.

• Select appropriate models and architectures while balancing accuracy, latency, cost, and complexity.

• Train and fine‑tune models using PyTorch or Keras, including data preparation and evaluation.

• Implement and benchmark research methods before adoption.

• Build APIs, inference pipelines, and backend integrations.

Production & Monitoring

• Own evaluation metrics and track quality, latency, and cost.

• Monitor, debug, and optimize AI systems post‑launch.

• Ensure production readiness and identify regressions before they impact users.

Collaboration

• Partner with software engineers and product teams to integrate AI into applications.

• Contribute to technical discussions and technical decision‑making.

• Document architecture, implementation approaches, and key technical decisions.

Research & Experimentation

• Read and evaluate ML research papers.

• Implement promising methods and reproduce results where applicable.

• Adapt emerging techniques into production‑ready systems.

• Contribute to continued innovation across AI and engineering initiatives.

Required Qualifications

• 3+ years of hands‑on AI/ML engineering experience, with at least one system deployed to production.

• Strong NLP fundamentals, including tokenization, embeddings, classification, NER, and information extraction.

• Strong engineering skills across coding, Git, testing, API/system design, and debugging.

• Hands‑on model training experience using PyTorch or Keras.

• Understanding of generative model architectures, including Transformers and VAEs.

• Production experience with LLMs, including RAG, embeddings/vector databases, and prompt/evaluation design.

• Experience with FastAPI or similar frameworks, Docker, and at least one cloud platform such as AWS, GCP, or Azure.

• Ability to read ML research papers and translate ideas into working code.

Preferred Qualifications

• Experience with LLM fine‑tuning, including LoRA and RL‑based methods.

• SQL database knowledge.

• Familiarity with agent frameworks such as LangGraph or LangChain.

• Experience with Kubernetes, CI/CD, and model‑serving infrastructure.

• Open‑source contributions or experience reproducing research results.

Working Relationships

The AI Engineer will collaborate with:

• Engineering leadership and product teams.

• Software engineers and backend developers.

• Global AI research and development teams.

Success in This Role

Success includes the ability to:

• Deliver production‑ready AI systems with measurable impact.

• Translate research into practical engineering solutions.

• Collaborate effectively across distributed teams.

• Document and share technical knowledge for scalability.

• Adapt to evolving technical and business priorities.

Compensation & Benefits

• Monthly Salary: PKR 150,000 – PKR 400,000, based on experience and technical expertise.

• Team members will be engaged by Volga Partners, with contract and payment administration facilitated through Deel.

• 90‑day probationary period.

• Benefits eligibility upon successful completion of the probationary period includes:

• Company‑sponsored medical insurance.

• Paid Time Off (PTO) in accordance with company policy.

• Holiday pay for company‐observed holidays.

• Career growth and professional development opportunities within Volga Partners’ growing AI‑focused organization.

Our Hiring Process

We value your time and aim to keep our recruitment process transparent, efficient, and engaging.

1. Initial Recruiter Screening

An introductory video call with a member of our Recruiting team to discuss your background, experience, career goals, salary expectations, and any initial questions you may have about the role or Volga Partners.

2. Practical Skills Assessment

Candidates who successfully complete the initial screening will receive a practical assessment to complete asynchronously.

The assessment is designed to evaluate technical knowledge, problem‑solving ability, and how you approach a real‑world engineering scenario.

3. Assessment Review

Our team will review your submission against the technical requirements of the role.

Candidates who meet the required criteria will advance to the final interview stage.

4. Final Interview – CTO

A deep‑dive conversation with our Chief Technology Officer focused on technical alignment, your assessment approach, architectural thinking, problem‑solving, and overall alignment with the role and team.