Architect

This is a fully remote position, open to applicants in New York.

📋 Description

• Establish agentic AI reference architectures encompassing LLM applications, RAG pipelines, tool/function invocation, memory systems, multi-agent orchestration, and enterprise integrations.

• Create and implement AI agents and autonomous workflows for Finance, Legal, Operations, Sales, Support, and Growth functions.

• Assess foundational models and enterprise AI platforms such as Gemini, Vertex AI, OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and various open-source LLMs.

• Connect AI solutions with Google Workspace, Slack, CRM systems, internal APIs, databases, and knowledge repositories.

• Apply observability, evaluation, guardrails, monitoring, reliability controls, and responsible AI practices for production applications.

• Assist clients in transitioning from AI experimentation to secure, scalable, production-ready agentic AI solutions.

• Enhance enterprise automation, developer productivity, operational efficiency, and time-to-market via reusable AI frameworks and contemporary engineering practices.

• Generate measurable business value through AI-first platforms that are aligned with customer success and engineering excellence.

⛳️ Requirements

• Over 8 years of experience in software engineering, solution architecture, enterprise architecture, or platform engineering.

• At least 2 years of practical experience in developing AI, GenAI, LLM-powered, or agentic applications.

• In-depth knowledge of LLMs, RAG, prompt engineering, vector databases, tool/function invocation, context management, memory systems, and AI workflow orchestration.

• Practical experience with LangChain, LangGraph, CrewAI, Google ADK, AutoGen, Semantic Kernel, or similar frameworks.

• Proficient engineering skills in Python and at least one of Java, Go, Node.js, React, TypeScript, APIs, microservices, SQL/NoSQL, and event-driven systems.

• Familiarity with Google Cloud, AWS, or Azure, including Docker, Kubernetes, CI/CD, DevSecOps, and cloud-native deployment patterns.

• Production deployment experience is preferred.

• Familiarity with AI evaluation frameworks, observability tools, guardrails, and feedback loops is advantageous.

• Knowledge of fine-tuning, model optimization, open-source LLM deployment, multi-agent coordination, and autonomous decision-making systems is a plus.

• Experience with Pinecone, Weaviate, Chroma, Vertex AI Vector Search, Google Workspace APIs, Slack integrations, or enterprise automation tools is a plus.

• Exposure to AI-driven SDLC tools, cloud certifications, open-source AI contributions, or fast-paced innovation environments is advantageous.

🏝️ Benefits

• Competitive salary and performance-based incentives.

• Comprehensive health, dental, and vision insurance.

• Flexible working hours and remote work options.

• Opportunities for professional development and continuous learning.

• Dynamic and inclusive work environment.