Design, build, and deploy agentic AI and multi-agent systems using LangChain/LangGraph and ADKs. Implement LLM orchestration, RAG pipelines, vector DBs, React-based AI interfaces, and production-grade infrastructure with observability, security, and optimization.
Key Responsibilities Agentic AI Development
Required Qualifications
- Design and implement autonomous AI agents capable of reasoning, planning, and executing multi-step workflows.
- Develop multi-agent systems that collaborate to solve complex tasks.
- Build tool-using agents that interact with APIs, databases, and enterprise services.
- Develop AI pipelines using LangChain, LangGraph, and related frameworks.
- Implement prompt engineering, memory systems, and reasoning chains.
- Integrate LLMs such as OpenAI, Anthropic, Gemini, or open-source models.
- Build production-ready agents using Agent Development Kits (ADK).
- Implement tool registries, agent planning systems, and execution loops.
- Develop modular agent architectures that support extensibility and reliability.
- Build interactive AI-driven user experiences using React Loop or similar frameworks.
- Design real-time interfaces for agent interaction, monitoring, and feedback loops.
- Implement streaming responses and agent status visualizations.
- Develop scalable AI services using Python (FastAPI, Flask, or similar).
- Integrate agents with vector databases, RAG pipelines, and knowledge graphs.
- Implement observability, evaluation, and guardrails for agent behavior.
- Optimize AI pipelines for latency, cost, and reliability.
- Ensure security, governance, and compliance for AI systems.
Required Qualifications
- 7+ years of software engineering experience.
- Strong expertise in Python for AI/ML development.
- Hands-on experience with LangChain / LangGraph.
- Experience building agentic AI systems or autonomous agents.
- Experience with React-based AI interfaces (React Loop or similar).
- Familiarity with vector databases (Pinecone, Weaviate, FAISS, etc.).
- Experience with ADK (Agent Development Kit) frameworks.
- Experience building multi-agent systems.
- Knowledge of RAG architectures and knowledge retrieval systems.
-
Compensation, Benefits and Duration
Minimum Compensation: USD 40,000
Maximum Compensation: USD 141,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
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