Senior AI Engineer

Systems Limited; Punjab; On-site; PKR 2,500,000 - 5,000,000; Full time

Job summary

Systems Limited is seeking a Senior AI Engineer to lead advanced AI initiatives in Pakistan's Punjab region. You will architect RAG-based retrieval, multi-turn conversational agents, and production-grade voice AI solutions with real-time speech and TTS/STT components.

The role emphasizes cloud and MLOps, deep LLM expertise, and scalable infrastructure for low-latency inference. A strong publication or open-source track is a plus, with collaboration across agile teams.

Qualifications

• 8+ years of software engineering experience with 4+ years focused on AI/ML engineering.
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow).
• Deep hands-on experience with advanced RAG systems, multi-stage retrieval, embedding models and vector search.
• Proven experience building conversational AI systems with intent recognition and memory management.
• Production experience with voicebot development including real-time audio processing and TTS/STT integration.
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
• Experience with MLOps tools and practices (MLflow, Weights & Biases, experiment tracking).
• Strong understanding of API design, microservices, and system integration.

Responsibilities

• Design and implement advanced Retrieval-Augmented Generation (RAG) systems with sophisticated chunking strategies, multi-vector retrieval, and hybrid search architectures.
• Develop and optimize conversational AI agents with complex multi-turn dialogue management and context awareness.
• Build production-ready voicebot solutions integrating real-time speech processing pipelines.
• Architect and deploy Text-to-Speech (TTS) and Speech-to-Text (STT) systems with low latency and high accuracy.
• Design and Deploy PROD grade AI Agents that can scale up for various use cases.
• Optimize model performance through prompt engineering, few-shot learning, and retrieval strategies.
• Implement evaluation frameworks and metrics for LLM outputs and conversational quality.
• Develop custom training pipelines for domain adaptation and specialized use cases.
• Design scalable AI infrastructure supporting real-time inference and high-throughput batch processing.
• Implement efficient vector databases and semantic search systems (Pinecone, Azure Search).
• Build monitoring and observability solutions for AI systems in production.
• Stay current with latest developments in LLM architectures, RAG techniques, and voice AI technologies.
• Experiment with emerging models and frameworks to evaluate applicability to business problems.
• Contribute to technical documentation, best practices, and knowledge sharing within the team.
• Prototype and validate new AI capabilities through POCs and pilots.

Skills

Python

PyTorch

TensorFlow

RAG

LLM integration

Vector search

AWS

GCP

Azure

Docker

Kubernetes

MLflow

Weights & Biases

CI/CD

Education

Master's or PhD in Computer Science/AI/ML

Tools

OpenAI / Anthropic / Cohere API integration

Pinecone / Azure Cognitive Search

LLM hosting frameworks

Job description

We are seeking an exceptional Senior AI Engineer to join our team and drive the development of cutting-edge AI solutions that includes conversational, Agentic AI's. This role focuses on building advanced conversational AI systems, implementation AI Agents across different use cases, implementing sophisticated RAG architectures, and deploying production-grade voice AI applications. The ideal candidate will have deep expertise in LLM technologies and a proven track record of delivering scalable AI solutions.

Responsibilities:

• Design and implement advanced Retrieval-Augmented Generation (RAG) systems with sophisticated chunking strategies, multi-vector retrieval, and hybrid search architectures
• Develop and optimize conversational AI agents with complex multi-turn dialogue management and context awareness
• Build production-ready voicebot solutions integrating real-time speech processing pipelines
• Architect and deploy Text-to-Speech (TTS) and Speech-to-Text (STT) systems with low latency and high accuracy
• Design and Deploy PROD grade AI Agents that can scale up for various use cases.
• Optimize model performance through prompt engineering, few-shot learning, and retrieval strategies
• Implement evaluation frameworks and metrics for LLM outputs and conversational quality
• Develop custom training pipelines for domain adaptation and specialized use cases
• Design scalable AI infrastructure supporting real-time inference and high-throughput batch processing
• Implement efficient vector databases and semantic search systems (Pinecone, Azure Search)
• Build monitoring and observability solutions for AI systems in production
• Stay current with latest developments in LLM architectures, RAG techniques, and voice AI technologies
• Experiment with emerging models and frameworks to evaluate applicability to business problems
• Contribute to technical documentation, best practices, and knowledge sharing within the team
• Prototype and validate new AI capabilities through POCs and pilots

Requirements:

• 8+ years of software engineering experience with 4+ years focused on AI/ML engineering
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow)
• Deep hands-on experience with advanced RAG systems:
• Multi-stage retrieval architectures (hybrid search, re-ranking)
• Embedding models and vector similarity search
• Document processing, chunking strategies, and metadata filtering
• Query understanding and retrieval optimization
• Proven experience building conversational AI systems:
• Intent recognition and slot filling
• Context tracking and memory management
• Integration with LLM APIs (OpenAI, Anthropic, Cohere, etc.)
• Production experience with voicebot development:
• Real-time audio streaming and processing
• Voice activity detection (VAD)
• End-to-end latency optimization
• Integration of STT, dialogue management, and TTS components
• Expertise in TTS and STT technologies:
• Audio preprocessing and enhancement
• Voice cloning and customization
• Strong experience with LLM fine-tuning:
• Proficiency with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
• Experience with MLOps tools and practices (MLflow, Weights & Biases, experiment tracking)
• Strong understanding of API design, microservices architecture, and system integration
• Knowledge of version control, CI/CD pipelines, and deployment automation
• Excellent analytical and debugging skills for complex AI systems
• Strong communication skills with ability to explain technical concepts to non-technical stakeholders
• Experience working in agile environments with cross-functional teams
• Self-motivated with ability to drive projects from conception to production
• Master's or PhD in Computer Science, AI/ML, or related technical field
• Experience with open-source LLMs (Llama, Mistral, etc.) and local deployment
• Knowledge of reinforcement learning from human feedback (RLHF) and DPO
• Familiarity with multi-modal AI systems (vision-language models, audio-visual understanding)
• Experience with real-time streaming architectures and WebRTC
• Published research or contributions to open-source AI projects
• Experience with GPU optimization and distributed training
• Knowledge of voice biometrics, speaker diarization, or emotion recognition
• Background in linguistics, phonetics, or speech processing