Senior Python Developer (AI Engineer)

TL;DR

Senior Python Developer (AI Engineer): Design and implement end-to-end LLM-powered applications, with a strong focus on Retrieval-Augmented Generation (RAG) pipelines. Focus on developing scalable vector database architectures, integrating AI platforms and APIs, and deploying production-ready AI systems in cloud environments.

Location: Remote (work from anywhere: home, beach, or office)

Company

Fast-growing strategic product and technology consultancy based in NYC, working with Fortune 500 companies and VC-backed startups on products users love.

What you will do

• Design and implement end-to-end LLM-powered applications with focus on RAG pipelines
• Build production-ready AI systems using Python and modern AI/ML frameworks
• Develop and optimize data ingestion, embedding pipelines, and semantic search workflows
• Design scalable vector database architectures and integrate AI platforms/APIs (e.g., OpenAI, Anthropic)
• Deploy and maintain AI solutions in cloud environments (AWS, Azure, GCP)
• Collaborate cross-functionally to translate business requirements into technical solutions
• Ensure code quality, testing, monitoring, performance optimization, and contribute to MLOps practices

Requirements

• Master’s degree in Computer Science, Engineering, AI, or related field
• 5+ years in AI/ML engineering or backend software engineering
• Proven experience building and deploying LLM applications, especially RAG-based systems
• Strong Python programming skills
• Experience with LLM APIs (e.g., OpenAI, Anthropic, Azure OpenAI)
• Solid knowledge of vector databases (e.g., Pinecone, Weaviate) and semantic search
• Experience with major cloud platform (AWS, Azure, or GCP) in production
• Understanding of APIs, microservices, scalable backend architecture, and production deployments

Nice to have

• Experience in AI system architecture design and technical standards
• Participation in AI roadmap and technical planning
• Designing/implementing multi-agent AI systems
• Alternative vector DBs (e.g., FAISS, Milvus), Hugging Face, fine-tuning open-source models
• Advanced MLOps, model governance, PhD in relevant field, mentoring juniors

Culture & Benefits

• Work on one project at a time with long-term engagements
• Flexible hours without time-tracking, remote from anywhere
• Indefinite period contract (B2B option), regular feedback, role switches supported
• Education opportunities (courses, conferences), monthly knowledge-sharing and brainstorming sessions
• Referral fees for successful recommendations