- Proven experience designing and deploying agentic AI systems using LLMs, vector databases, and orchestration frameworks like LangGraph or LangChain
- Deep understanding of LLM tool use, memory management, retrieval-augmented generation (RAG), and multi-agent collaboration
- Strong ability to work with cross-functional stakeholders to define and implement scalable, extensible AI architectures
- Experience building stateful, goal-driven agents that can reason, plan, and act autonomously in complex environments
- Passion for building human-centric AI that is ethical, explainable, and aligned with user needs and regulatory standards
- Excellent communication and evangelism skills to influence technical direction and promote best practices
Responsibilities Include:
- Architect and implement agentic AI chat systems that integrate LLMs with tools, APIs, and memory for dynamic task execution
- Design and develop LangGraph-based workflows for orchestrating multi-step, multi-agent interactions
- Collaborate with Product Managers, Architects, and Engineering Leads to define AI capabilities and roadmap
- Build and maintain reference architectures, POCs, and technical documentation to guide engineering teams
- Ensure AI systems meet non-functional requirements such as performance, scalability, observability, and security
- Mentor engineers and foster a culture of innovation, experimentation, and continuous learning in GenAI
- Advocate for responsible AI practices, ensuring compliance with PII/PHI handling, ADA, and other regulatory standards
- Stay current with advancements in LLMs, agentic frameworks, and AI safety to inform strategic decisions
REQUIRED QUALIFICATIONS
- 10+ years of software engineering experience, with 3+ years in AI/ML or LLM-based application development
- 2+ years of hands-on experience with LLM orchestration frameworks (e.g., LangGraph, LangChain, Semantic Kernel)
- 2+ years of experience building agentic AI systems or autonomous agents using OpenAI, Anthropic, or open-source LLMs
- Strong proficiency in Python, FastAPI, vector databases (e.g., FAISS, Weaviate), and RAG pipelines
- Experience with cloud platforms (GCP preferred), microservices, and API-first development
- Familiarity with CI/CD, DevOps, and observability tools for AI systems
PREFERRED QUALIFICATIONS
- Experience with LangGraph or similar graph-based agent orchestration tools
- Knowledge of LLMOps, prompt engineering, and fine-tuning or RAG optimization
- Experience with chatbot frameworks, voice assistants, or multimodal agents
- Background in healthcare, HIPAA compliance, or regulated AI systems
- Strong understanding of AI safety, alignment, and ethical AI design
- Excellent communication and presentation skills