AI Engineer

2 weeks ago

Karachi, Sindh, Pakistan Xynotech Full time 1,200,000 - 3,600,000 per year

We're looking for a hands-on AI Engineer to join our team and help build the next generation of conversational AI systems. You'll play a key role in evolving our AI Engine that powers intelligent assistants using LLMs, hybrid search, memory abstraction, and lightweight ML components.

If you're passionate about LLM-powered agents, hybrid retrieval systems, and building modular AI architectures that can solve real-world business problems — this is your chance to make a deep impact.

What You'll Actually Do Here

  • Design, develop, and continuously improve LLM-driven conversational agents with intelligent reasoning capabilities
  • Build in-memory and hybrid memory architectures for handling both short-term and long-term context
  • Implement planner modules that route user intents and orchestrate tool and data access
  • Integrate retrieval systems like Elasticsearch, Pinecone, or Weaviate for structured and semantic search
  • Train and deploy lightweight machine learning models (e.g., classifiers, re-rankers) to complement LLM behavior
  • Build systems that support complex use cases like product recommendations, order management, and pricing queries
  • Collaborate with product and engineering teams to connect the AI layer with internal tools such as CRMs and web applications
  • Monitor and improve the performance, latency, and hallucination behavior of conversational agents using fallback strategies and evaluators
  • Stay up to date with trends in LLM applications, prompting strategies, distillation, and retrieval-augmented generation (RAG)

What You'll Bring To Us

  • Proficiency in Python or
  • Hands-on experience working with LLM APIs (OpenAI, Claude, Gemini, etc.)
  • Strong understanding of embedding models (e.g., Sentence Transformers, OpenAI, Cohere) and ANN search engines
  • Familiarity with structured prompting, function calling APIs, and few-shot learning methods
  • Experience designing modular AI systems with chaining, planner/executor logic, and context-aware flows
  • Exposure to training or deploying custom ML models (e.g., ranking models, classifiers)
  • Solid understanding of machine learning fundamentals and experience building AI-driven prototypes
  • Ability to thrive in ambiguous environments, rapidly experiment, and drive innovation

Our Toolkit

  • Languages & Frameworks: Python, TypeScript,
  • LLMs & APIs: OpenAI, Claude, Gemini
  • Embeddings & Vector Search: Sentence Transformers, Cohere, Pinecone, Weaviate, Elasticsearch
  • ML & Infrastructure: Hugging Face, custom ranking models, lightweight deployable classifiers
  • Orchestration Tools: LangChain, LangGraph, custom chaining frameworks

Even Better If You Have

  • Experience with LangChain, Haystack, or custom AI orchestration tools
  • Knowledge of fine-tuning, quantization, or distillation techniques (HuggingFace, LoRA)
  • Background in building recommendation systems or re-ranker models
  • Familiarity with voice interfaces (TTS/STT) or social platforms (e.g., WhatsApp Cloud API)
  • Understanding of AI reliability, fallback design, and real-world performance evaluation

What We Really Value

  • We're especially interested in engineers who:
  • Think like product builders, not just model tweakers
  • Understand that LLMs are powerful, but not always the answer
  • Are focused on real-world usability, not just prototypes
  • Pay attention to edge cases, testing, and failure modes
  • Communicate clearly with cross-functional teams and stakeholders

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