Senior AI Engineer
Quick Summary
ROKO Labs is a fast-growing strategic product and technology consultancy based in NYC. We are seeking a highly motivated and resourceful person who enjoys solving complex problems! We have a great track record of working with large Fortune 500 companies and VC-backed start-ups.
Design and implement end-to-end LLM-powered applications, with a strong focus on Retrieval-Augmented Generation (RAG) pipelines Build production-ready AI systems using Python and modern AI/ML frameworks Develop and optimize data ingestion, embedding…
Master’s degree in Computer Science, Engineering, AI, or a related field 7+ years of experience in backend software engineering with the latest 1-2 years developing and implementing AI-powered solutions Proven hands-on experience building and…
ROKO Labs is a fast-growing strategic product and technology consultancy based in NYC. We are seeking a highly motivated and resourceful person who enjoys solving complex problems! We have a great track record of working with large Fortune 500 companies and VC-backed start-ups. We are incredibly proud of our work and would be excited to share it with you! Our clients value that we understand their businesses and help to build products that users love! Additionally, our extended team spans multiple countries, making for fun cultural exchanges.
We are seeking an experienced Senior AI Engineer to lead the design and implementation of scalable, production-ready AI solutions that drive business value. This role combines architectural thinking with strong hands-on technical execution and business alignment. The ideal candidate is not only capable of defining AI architecture and best practices to ensure that the initiatives deliver measurable business impact, but is also comfortable building, testing, and deploying solutions directly. You will work cross-functionally with engineering, data, product, and business teams to translate requirements into robust AI systems.
Requirements
~1 min readResponsibilities
~1 min read- →Design and implement end-to-end LLM-powered applications, with a strong focus on Retrieval-Augmented Generation (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 and implement scalable vector database architectures
- →Integrate and work with selected AI platforms and APIs (e.g., OpenAI, Anthropic, Azure OpenAI)
- →Deploy and maintain AI solutions in cloud environments (AWS, Azure, or GCP)
- →Collaborate with product and engineering teams to translate business requirements into scalable technical solutions
- →Ensure code quality, testing, monitoring, and performance optimization of AI systems in production
- →Contribute to MLOps practices including CI/CD pipelines, model lifecycle management, and observability
- →Document technical decisions and implementation details
Requirements
~1 min read- Master’s degree in Computer Science, Engineering, AI, or a related field
- 7+ years of experience in backend software engineering with the latest 1-2 years developing and implementing AI-powered solutions
- Proven hands-on experience building and deploying LLM applications, especially RAG-based systems
- Strong programming skills with the following order of preference regarding languages: Python > .NET > TypeScript > Java
- Experience integrating LLM APIs (e.g., OpenAI, Anthropic, Azure OpenAI)
- Solid understanding of vector databases (e.g., Pinecone or Weaviate) and semantic search architectures
- Experience with at least one major cloud platform (AWS, Azure, or GCP) in production environments
- Understanding of APIs, microservices, and scalable backend architecture
- Experience deploying applications to production environments
- Strong problem-solving skills and ability to work in a fast-evolving AI landscape
Nice to Have
~1 min read- Experience contributing to AI system architecture design and technical standards
- Experience participating in AI roadmap discussions and technical planning
- Experience designing or implementing multi-agent AI systems
- Experience with alternative vector databases (e.g., FAISS, Milvus)
- Experience with Hugging Face ecosystem or fine-tuning open-source models
- Hands-on experience with advanced MLOps frameworks and model governance
- PhD (completed or in progress) in a relevant field
- Experience mentoring junior engineers or leading smaller technical initiatives
What We Offer
~2 min readLocation & Eligibility
Listing Details
- Posted
- April 3, 2026
- First seen
- May 6, 2026
- Last seen
- May 8, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 21%
- Scored at
- May 6, 2026
Signal breakdown
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