Artificial Intelligence Engineer

2 weeks ago

Karachi, Sindh, Pakistan Xynotech Full time $120,000 - $200,000 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

  • Bachelor's Degree
    in Computer Science or related field.
  • Minimum 3+ years of experience in AI Engineering
    .
  • 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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