Note: The job is a remote job and is open to candidates in USA. Photon is seeking a highly skilled AI Engineer proficient in Python to lead the technical development of their Agentic AI platform. The role involves designing architectures for autonomous systems, optimizing RAG pipelines, and building complex agentic workflows to enhance agent performance and reliability.
Responsibilities
- Build and maintain complex agentic workflows using frameworks like LangGraph, CrewAI, or AutoGen
- Develop Python-based tools and 'plugins' that agents can invoke to perform real-world actions (e.g., querying SQL databases, interacting with APIs, or executing code)
- Architect and optimize Retrieval-Augmented Generation (RAG) systems using vector databases to provide agents with long-term memory and domain-specific knowledge
- Implement and fine-tune reasoning patterns such as React (Reason + Act), Chain-of-Thought, and Plan-and-Solve to improve agent reliability
- Build automated testing frameworks to measure agent performance, accuracy, and 'drift' using tools like LangSmith or custom evaluation harnesses
- Optimize for latency and cost by managing token usage, implementing intelligent caching, and selecting the right model for the right task
Skills
- Proficient in Python
- Experience in building sophisticated autonomous systems
- Ability to design architecture for multi-step tasks
- Experience accessing external databases via RAG
- Ability to interact with third-party software through function calling
- Experience in building and maintaining complex agentic workflows using frameworks like LangGraph, CrewAI, or AutoGen
- Develop Python-based tools and plugins for agents
- Architect and optimize Retrieval-Augmented Generation (RAG) systems using vector databases
- Implement and fine-tune reasoning patterns such as React (Reason + Act), Chain-of-Thought, and Plan-and-Solve
- Build automated testing frameworks to measure agent performance, accuracy, and drift
- Optimize for latency and cost by managing token usage and implementing intelligent caching
- Deep experience in asynchronous Python
- Experience with Pydantic for data validation
- Experience with FastAPI for building robust service layers
- Hands-on experience with LangChain, LlamaIndex, or specialized orchestration libraries
- Deep understanding of LLM capabilities (OpenAI, Anthropic, Gemini)
- Experience with local model deployment (Ollama, vLLM)
- Proficiency with vector databases (Pinecone, Weaviate, Milvus, or Chroma)
- Proficiency with traditional relational databases (PostgreSQL)
- Experience with CI/CD, Docker, and monitoring tools
- Experience with multi-agent systems where different agents have specialized roles and hand-off protocols
- Contributions to open-source AI projects or a strong portfolio of Agentic AI experiments on GitHub
- Knowledge of fine-tuning techniques (LoRA, QLoRA) for specific domain tasks
Benefits
- Medical, vision, and dental benefits
- 401k retirement plan
- Variable pay/incentives
- Paid time off
- Paid holidays
Company Overview
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