Job Details

We’re Hiring: AI Engineer

Company: Musketeers Tech Pvt. Ltd.

Location: On-site, Gulberg II, Lahore

Employment Type: Full-time

Role Overview

As an AI Engineer at Musketeers Tech, you’ll contribute to LLM/GenAI feature development, RAG systems, LLMOps and evaluation, and production backend engineering. You’ll also gain guided exposure to self-hosted inference stacks and fine-tuning workflows, supporting model release processes and quality gates.

Core Responsibilities

1) LLM/GenAI Feature Development

Build LLM-powered product features, including chat/assistants, information extraction, summarization, classification, semantic search, and Q&A.

Implement Retrieval-Augmented Generation (RAG) pipelines (with guidance), including:

Chunking strategies, metadata design, and embedding generation

Retrieval approaches (vector search + keyword search where needed) and basic re-ranking

Prompt/context optimization, caching strategies, and citations/attribution patterns

Implement tool-using LLM flows, including:
Function calling and structured outputs (JSON schema)

Simple multi-step agent workflows (orchestration, state passing)

Guardrails fundamentals: prompt-injection awareness and safe tool usage

2) Self-Hosting & Fine-Tuning Exposure (Guided)

Help run and integrate self-hosted inference stacks such as Ollama, vLLM, TGI, and llama.cpp (or similar).

Assist with serving optimization, including:

Batching/streaming basics, concurrency testing, and latency profiling

Quantized formats (e.g., GGUF/AWQ/GPTQ) and deployment configuration

Support fine-tuning workflows as needed:

Dataset preparation (cleaning, formatting for instruction tuning)

Basic LoRA/QLoRA experiments, tracking, and reproducibility

Learn and follow Musketeers Tech’s model release workflow: versioning, evaluation gates, and rollback procedures.

3) Evaluation, Quality & LLMOps

Contribute to evaluation harnesses and automated quality checks:

Build/maintain golden datasets and regression tests

Implement auto-scoring plus human review loops

Track and improve operational metrics including:

Latency, error rates, cost per request, retrieval hit rate and answer quality

Participate in prompt/model versioning and safe rollout practices.

4) Production Engineering (Backend + DevOps Basics)

Build and maintain APIs and services (e.g., FastAPI/Flask): auth basics, rate limits, caching, async jobs/queues.

Containerize services using Docker and contribute to CI/CD pipelines.

Add observability: structured logging, baseline metrics, and tracing when required.

5) Security & Privacy Basics

Follow secure engineering practices: secrets management, access control, and PII handling.

Understand AI-specific risks: prompt injection, tool data leakage, and unsafe output pathways.

Required Qualifications (Must Have)

1+ year of experience building software systems (professional or strong project portfolio).

Strong Python fundamentals (functions, OOP, typing basics, debugging, testing mindset).

Basic understanding of LLMs + RAG:

embeddings, chunking, vector search concepts

at least one working RAG or LLM project (personal/professional)

Experience building APIs (FastAPI/Flask/Django) or similar backend services.

Familiarity with Git + Docker; comfortable deploying/running services locally and in staging.

Soft Skills

Strong problem-solving and critical-thinking skills.

Effective communication and team collaboration abilities.

Eagerness to learn and adapt to emerging technologies.

Ability to manage time and prioritize tasks in a dynamic, collaborative environment.

Become a part of Musketeers Tech—where innovation, growth, and teamwork go hand in hand.