Senior AI Engineer
2 weeks ago
The Sr. AI Engineer will design, architect, and implement
advanced AI systems
leveraging
multi-agent frameworks
,
RAG pipelines
, and
LLM orchestration layers
. You'll be responsible for building intelligent, scalable workflows that enable reasoning, contextual understanding, and autonomous task coordination across various enterprise use cases.
Key Responsibilities
- Architect and deploy multi-agent AI systems using frameworks like LangGraph, CrewAI, or custom orchestrators.
- Design and optimize Retrieval-Augmented Generation (RAG) pipelines for contextual reasoning and dynamic knowledge synthesis.
- Integrate vector databases and semantic search layers (e.g., Pinecone, Weaviate, FAISS) for efficient knowledge retrieval.
- Develop modular LLM pipelines combining tools, memory, and dynamic context switching.
- Implement Python-based AI microservices with robust APIs for reasoning, planning, and data processing.
- Conduct prompt engineering, evaluation, and adaptive tuning to improve model accuracy and reliability.
- Build autonomous data ingestion and learning loops to continuously improve AI system performance.
- Collaborate with cross-functional teams to align AI pipelines with product goals and business logic.
- Research and prototype new frameworks in agentic AI, self-correcting systems, and multi-modal reasoning.
Required Skills
- Minimum 5+ years of experience
- Strong expertise in LLMs, NLP, RAG architectures, and multi-agent orchestration.
- Proficiency in Python, LangChain, LangGraph, and OpenAI / Hugging Face APIs.
- Experience deploying AI pipelines in production environments (microservices or distributed systems).
- Hands-on with vector DBs, semantic embeddings, and knowledge graphs.
- Solid grasp of LLM evaluation, memory management, and context-aware reasoning.
- Experience integrating AI tools with backend systems (e.g., GitHub, Azure DevOps, RESTful APIs and FASTAPIs).
- Strong understanding of system design, data pipelines, and cloud-based AI architectures.
Nice to Have
- Familiarity with LangGraph, CrewAI, LlamaIndex, or Semantic Kernel.
- Experience building autonomous agents or self-improving task networks.
- Exposure to Azure OpenAI, Vertex AI, or Anthropic Claude API.
- Background in AI evaluation, reinforcement learning from human feedback (RLHF), or tool-augmented reasoning.
- Ability to mentor teams in prompt engineering, AI safety, and agentic framework design.
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