bayt
AI Engineer
Intelligence Experts
Doha, QAT
Full Time
Mid
Onsite
QAR 14,815 QAR 18,519
2 months ago
PythonLangGraphLangChainLangFuseFastAPIReact
Free
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PythonLangGraphLangChain
About the Role
Intelligence Experts is seeking an AI Engineer to design and build multi-agent AI systems for a large pharmaceutical environment, using LangGraph, LangChain, and LangFuse.
Key Skills for This Role
PythonLangGraphLangChainLangFuseFastAPIReact
Responsibilities
- Design and evolve the core agentic architecture supporting multi agent workflows
- Write production quality Python code for critical agent components
- Build LangGraph state management, checkpoint services, and session handling
- Develop data agents for SQL query generation, semantic validation, document parsing, embedding, and knowledge graph traversal
- Implement sophisticated prompt engineering for SQL generation, synthesis, and reasoning tasks
- Build and maintain full stack features using Python backend services and React frontend interfaces
- Design and implement integrations with Snowflake, Neo4j, ChromaDB, Azure AI services, and AWS AI stack
- Manage and improve deployment pipelines using Docker, Kubernetes, and CI/CD automation
Requirements
- Master's degree or PhD in AI, Data Science, Computer Science, Machine Learning, or a similar field
- 3+ years of professional Python development
- Hands on experience with FastAPI, Flask, or similar frameworks
- Experience with agentic frameworks such as LangGraph, LangChain
- Experience with cloud data infrastructure (Snowflake, Neo4j, vector databases)
Full Job Posting
Position Overview
- We are seeking an exceptional AI Engineer to design, build, and evolve sophisticated multi agent AI systems for a large pharmaceutical industry environment.
- This role focuses on production grade agentic AI, manufacturing intelligence, quality control, and operational analytics across complex pharmaceutical operations.
Key Responsibilities
- Design and evolve the core agentic architecture supporting multi agent workflows, including planning, data fetching, synthesis, analysis, and reporting.
- Define state management patterns, checkpoint strategies, and memory systems for long running agent conversations.
- Architect Human in the Loop integration patterns for quality assurance and risk mitigation.
- Establish best practices for agent composition, tool design, and inter agent communication.
- Create technical roadmaps that balance innovation with production stability.
- Write production quality Python code for critical agent components.
- Build LangGraph state management, checkpoint services, and session handling.
- Develop data agents for SQL query generation, semantic validation, document parsing, embedding, and knowledge graph traversal.
- Develop orchestration agents for task planning, dependency management, and workflow coordination.
- Build analysis agents for visualization generation, anomaly detection, and ML driven insights.
- Implement sophisticated prompt engineering for SQL generation, synthesis, and reasoning tasks.
- Build robust validation pipelines, including SQL injection prevention, schema validation, and result sanity checks.
Framework and Stack Expertise
- Support adoption and optimization of LangGraph, LangChain, LangFuse, and Deep Agents.
- Work with LangGraph for multi agent state machines, graph based workflows, and parallel execution patterns.
- Work with LangChain for tool definitions, chains, retrieval augmented generation, and agent workflows.
- Work with LangFuse for agent tracing, observability, and performance analytics.
- Apply advanced agentic patterns including reflection, planning, and tool use optimization.
- Maintain deep knowledge of emerging agentic frameworks and contribute to technology evaluation.
- Guide technology choices, including when to use LLMs vs. SLMs, caching strategies, and cost optimization.
Cloud and Data Infrastructure
- Design and implement integrations with Snowflake, Neo4j, ChromaDB, Azure AI services, and AWS AI stack.
- Work with Snowflake for query optimization, cost control, and schema design.
- Work with Neo4j for semantic search, relationship modeling, and document discovery.
- Work with vector stores such as ChromaDB, Pinecone, or Weaviate for embedding management, semantic indexing, and RAG optimization.
- Architect file system abstraction layers for Azure Blob Storage, S3, and local storage.
- Design and optimize database schemas for checkpoint persistence and result tracking.
- Implement connection pooling, caching strategies, and performance optimization.
Collaboration and Knowledge Sharing
- Collaborate with AI engineers, data engineers, ML researchers, manufacturing teams, and business stakeholders.
- Conduct code reviews with attention to architectural consistency and quality.
- Pair program on complex implementations, including prompt engineering, agent coordination, and validation.
- Share knowledge through documentation, architecture decision records, and technical discussions.
- Contribute to engineering practices, including testing strategies, deployment procedures, and incident response.
Quality, Testing, and Reliability
- Design comprehensive validation frameworks.
- Build unit tests for agent components with mocked LLM responses.
- Build integration tests for multi agent workflows.
- Build end to end tests simulating real manufacturing queries.
- Implement safety guardrails including SQL injection prevention, query cost estimation, and anomaly detection.
- Establish error handling and graceful degradation patterns.
- Drive observability through structured logging, distributed tracing, and performance dashboards.
Production Operations and Optimization
- Manage and improve deployment pipelines using Docker, Kubernetes, and CI/CD automation.
- Monitor system health, latency, and cost metrics post launch.
- Implement observability dashboards using LangFuse, Prometheus, and custom analytics.
- Optimize performance through LLM caching, query batching, and result streaming.
- Support incident response for agent failures, data quality issues, and system degradation.
Preferred Qualifications
- Familiarity with academic agentic AI research papers.
- Contributions to AI/ML open source projects.
- Participation in AI communities, research communities, or technical forums.
- Manufacturing, supply chain, pharmaceutical, or quality control domain knowledge.
- Experience with anomaly detection or time series analysis.
- Knowledge of data quality frameworks and validation patterns.
- Machine learning model development and evaluation.
- NLP and embeddings experience, including Hugging Face and sentence transformers.
- Real time data processing with Kafka, Flink, or similar technologies.
- Database performance tuning and query optimization.
What We Are Building
- The AI Engineer will help build a sophisticated multi agent agentic system for a large pharmaceutical industry environment.
- The system includes 10 major components across 12 execution phases: Input Processing, Memory and State, Planning, Data Agents, Human in the Loop, Synthesis, Analysis Planning, Visualization Agent, ML Analysis Agent, Report Assembly, Checkpoint Persistence, Suggested Questions.
- Technical Stack: Core: Python 3.10+, FastAPI, Pydantic, React; Frontend: React, JavaScript or TypeScript, data dashboards, API driven user interfaces; Agentic Frameworks: LangGraph, LangChain, LangFuse, Deep Agents; Data: Snowflake, Neo4j, ChromaDB, PostgreSQL for checkpoints, Redis for caching; Clo
Required Qualifications
- Master's degree or PhD in AI, Data Science, Computer Science, Machine Learning, or a similar field.
- 3+ years of professional Python development.
- Comfortable with async/await, type hints, and modern Python idioms.
- Hands on experience with FastAPI, Flask, or similar frameworks.
- Full stack Python development experience, including backend API design, service integration.
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