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Generative AI Engineer

2 weeks ago

Lahore, Punjab, Pakistan Tkxel Full time $125,000 - $175,000 per year
We are seeking a Generative AI Engineer

Core Responsibilities

Multi-Agent System Architecture

  • Architect and implement multi-agent workflows using LangChain, LangGraph, AutoGen, CrewAI, Google ADK, CAMEL, Swarm, and OpenAI Agents SDK to orchestrate task decomposition, memory, tool use, and agent coordination.

Model Context Protocol (MCP) Integration

  • Engineer workflows that use MCP for context-sharing and standardized communication among agents and with external systems (SQL, file systems, tools).

Agent Framework Development

  • Design abstracted agent frameworks supporting planning, reasoning, retries, orchestration, and observability.

Data Processing & Pipelines

  • Develop ETL pipelines for ingestion, transformation, storage, and embedding generation using Airflow, Prefect, Spark, Hadoop, and vector databases (FAISS, Pinecone, Weaviate).

LLM Fine‑Tuning & RAG Architecture

  • Fine‑tune GPT, LLaMA, Claude, Mistral models with efficient methods; build retrieval‑augmented systems using vector DBs and knowledge graphs.

Multimodal AI & API Integration

  • Integrate text, image, audio, OCR, and structured data (via CLIP, Whisper, TTS/STT); expose capabilities through REST/GraphQL APIs and microservices.

Production MLOps & Engineering

  • Follow core Python engineering practices—OOP, async, unit testing, packaging. Containerize with Docker and deploy on Kubernetes or serverless infra.

Ethics, Security & Performance Optimization

  • Integrate bias detection, explainability, privacy safeguards (prompt injection mitigation), and optimize performance and cost.

Education:

  • BSc or MSc in Computer Science, Engineering, Data Science, or equivalent.

Technical Skills:

  • Python: Advanced proficiency in OOP, async programming, packaging, testing.

  • LLM Frameworks: Hugging Face Transformers, PyTorch, TensorFlow.

  • Agent Frameworks: Experience with LangChain, LangGraph, AutoGen, CrewAI, ADK.

  • Protocols: Deep understanding of MCP, A2A, and agent interoperability.

  • Data Engineering: Airflow, Prefect, Spark/Hadoop, SQL/NoSQL, vector databases.

  • Cloud & Containerization: Experience with AWS, GCP, Azure, Docker, Kubernetes.

  • API & Microservices: FastAPI, Flask, GraphQL, event-driven systems.

  • RAG Systems: Expertise in FAISS, Pinecone, ChromaDB, Weaviate, and knowledge graphs.

  • Software Quality & Architecture: Strong foundations in system design, scalability, security, and CI/CD best practices.

  • Proven track record in full-stack AI agent deployment.

  • Deep familiarity with prompt engineering, decision chaining, and tool integrations.

  • Background in reinforcement learning, planning, or control-loop architectures.

Soft Skills:

  • Excellent communication and collaboration across multidisciplinary teams.

  • Analytical mindset with strong debugging and iterative development approach.

  • Agile-oriented: rapid experimentation, evaluation, and adaptation.