Overview In this role, you design and guide end-to-end AI platform architectures that weave together LLMs, data pipelines, and enterprise systems. You work across AI, data, product, and engineering teams to deliver scalable, agentic AI solutions. You prototype and validate architectures, and mentor teams while translating complex concepts for stakeholders. This is a chance to shape AI platform patterns at scale in a collaborative, growth-minded environment.
Compensation / Benefits- Zero dollar health insurance premiums for employees and dependents
- Dental coverage up to $5,000 orthodontia
- Vision insurance
- Gym membership reimbursement
- Fully vested retirement contributions
- Generous paid time off and office closure during holidays
Responsibilities- Design AI and LLM-based system architectures with emphasis on scalability, performance, and maintainability
- Evaluate and select AI frameworks and tooling to fit use cases (e.g., LangChain, LlamaIndex, LangGraph, Semantic Kernel)
- Create agentic AI solutions for workflow automation including memory usage and orchestration patterns
- Define integration patterns (RAG, context management, prompts, enterprise connectivity) and lifecycle governance
- Develop proof-of-concepts and architectural prototypes for AI platforms and agent orchestration
- Support production deployment, observability, and governance for scalable solutions
- Define development standards for versioning, testing, deployment, and LLMOps
- Communicate technical designs clearly to both technical and non-technical stakeholders
- Lead and mentor junior architects and technology consultants to ensure architectural alignment
- Contribute to business development through architecture input and solution shaping
Key requirements- 6+ years in software/data engineering or AI systems with architecture/leadership experience
- Strong software architecture and distributed systems foundation
- Experience designing AI/ML or LLM-based systems in production or near-production
- Programming experience (Python, JavaScript, TypeScript) preferred
- Familiarity with AI-assisted coding tools and rapid prototyping
- Experience with agentic AI frameworks (LangChain, LangGraph, Semantic Kernel, AutoGen, LlamaIndex)
- Knowledge of RAG, multi-agent orchestration, memory patterns, vector databases, function-calling
- Cloud architecture and API integration (AWS, Azure, GCP); cloud AI deployments
- Containerization/orchestration (Docker, Kubernetes)
- Exposure to vector databases (Pinecone, Qdrant, Aure) or similar
- Strong analytical and communication skills; consulting mindset; travel willingness
- Gen AI fluency and validation of AI outputs
- Collaborative and stakeholder-oriented
- Clear communicator for technical and non-technical audiences
- Ambiguity-tolerant and agile in delivery
- LangChain
- LlamaIndex
- LangGraph
