We are looking for an innovative AI Engineer to architect and deploy cutting-edge agentic AI systems—autonomous, goal-driven agents that reason, plan, and execute complex tasks with minimal human oversight. You will work at the intersection of software engineering and advanced AI, building scalable multi-agent workflows that integrate seamlessly into enterprise ecosystems.

This is an opportunity to shape the future of autonomous AI systems, working with state-of-the-art LLMs and orchestration frameworks to solve real-world business challenges.

What You'll Do

Architect Agentic AI Systems

• Design and build multi-agent frameworks leveraging patterns
• Develop autonomous reasoning modules powered by advanced LLMs (GPT-4/5, Claude, Falcon)
• Create goal-directed agents capable of dynamic decision-making and self-correction

Engineer Context & Memory Systems

• Implement sophisticated context management strategies including dynamic injection, retrieval-augmented generation (RAG), and long-term memory architectures
• Build safety guardrails and coherence mechanisms to ensure reliable agent behavior
• Design prompt engineering pipelines optimized for multi-turn, complex task execution

Orchestrate Complex Workflows

• Build end-to-end pipelines for multi-step task execution, tool integration, and iterative refinement
• Develop coordination mechanisms for multi-agent collaboration and task delegation
• Implement feedback loops and self-improvement mechanisms

Deploy Production-Ready Solutions

• Integrate agents with enterprise APIs, vector databases, and third-party systems
• Containerize and deploy using Docker with CI/CD pipelines
• Ensure secure, compliant, and fault-tolerant execution in production environments

Ensure Performance & Safety

• Build comprehensive observability frameworks with tracing, logging, and performance monitoring
• Implement ethical AI safeguards including human-in-the-loop checkpoints and bias detection
• Optimize for scalability, latency, and resource efficiency across distributed systems

Required Qualifications

Technical Expertise

• Strong Python proficiency with production-level code quality
• Deep experience with agentic AI frameworks: LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar
• Hands-on work with LLMs (GPT-4/5, Claude, Mistral, or Falcon) and fine-tuning techniques
• Proven ability to implement RAG systems, embedding models, and vector search

AI & ML Fundamentals

• Solid understanding of multi-agent orchestration patterns and coordination mechanisms
• Expertise in prompt engineering, context window management, and token optimization
• Knowledge of memory systems (semantic, episodic, procedural) and state management

Infrastructure & Data

• Experience with vector databases (FAISS, Milvus, Pinecone, Weaviate)
• Familiarity with embedding models and semantic search pipelines
• Understanding of observability tools and telemetry systems

AI Safety & Ethics

• Awareness of hallucination mitigation techniques and output validation strategies
• Knowledge of compliance frameworks (GDPR, HIPAA, SOC 2) as they apply to AI systems
• Commitment to responsible AI development practices

Preferred Qualifications

• 5+ years of experience in AI/ML engineering roles
• 2+ years specifically working with Agentic AI, autonomous systems, or multi-agent frameworks
• Production deployment experience in cloud environments (Azure, AWS, GCP)
• Python expertise is required
• RUST experience is a plus
• Contributions to open-source AI projects is a plus
• Experience with ML-Ops practices, model monitoring is a plus
• Background in reinforcement learning is a plus
• Hands on experience with Claude.AI LLM models is a plus