Note: The job is a remote job and is open to candidates in USA. Blockchains, Inc. is focused on creating a future where individuals have control over their digital identities through innovative AI solutions. As a Senior AI Engineer, you will be responsible for making technical decisions regarding AI systems, designing architecture, and ensuring privacy and safety in AI implementations. Your role will involve integrating LLMs, optimizing AI pipelines, and collaborating on security measures.

Responsibilities

• Architecting context augmentation pipelines: vector RAG, CAG, agentic file exploration, Text-to-SQL, knowledge graphs, fine-tuning, or MCP-based context engineering, selecting the right approach for each use case
• Designing chunking strategies, embedding model selection, and retrieval architecture for user-owned document systems with multi-tenant isolation
• Owning data privacy at the systems level: PII handling, GDPR/CCPA compliance, encryption at rest and in transit, and user-scoped access boundaries
• Integrating and managing LLM APIs (such as OpenAI, Anthropic, or open-source models) and deploying multi-agent systems using LangChain, LlamaIndex, or LangGraph
• Leading model selection, prompt engineering, fine-tuning (LoRA/QLoRA), and production evaluation across the AI stack
• Building evaluation frameworks to measure output quality, relevance, and safety, moving beyond vibes-based testing to systematic, repeatable evals
• Optimizing AI pipelines for latency, token cost, and throughput; monitoring production systems for drift, degradation, and regressions
• Defining and implementing feedback loops that connect evals back to iteration, making AI system performance visible and continuously improving in production
• Deploying and operating production AI systems on AWS, Docker/Kubernetes, and GitLab
• Defining AI service contracts and APIs that front-end and product engineers build on top of
• Collaborating with Information Security on AI security posture: data exposure risk, agentic workflow guardrails, and shadow AI detection

Skills

• At least 2 years of experience building and shipping production AI systems
• A minimum of 5 years of software engineering experience
• Strong Python skills
• Deep knowledge of LLMs (such as GPT-4, Claude, Llama, or Mistral), spanning prompt engineering, fine-tuning, and production evaluation
• Hands-on experience designing context augmentation systems: vector RAG (hybrid search, re-ranking, multi-tenant isolation), CAG, agentic file exploration, Text-to-SQL, knowledge graphs, fine-tuning, and MCP-based context engineering
• Strong command of agent orchestration frameworks, including LangChain, LlamaIndex, or LangGraph
• Experience building or using evaluation frameworks to measure LLM output quality, relevance, and safety in production
• Deep understanding of data privacy at the infrastructure level, including PII handling, GDPR/CCPA compliance, and encryption at rest and in transit
• Hands-on experience with AWS (ECS, EKS, Lambda, S3, Bedrock), Docker, Kubernetes, and GitLab
• Experience with Node.js or .NET
• A bachelor's degree in Computer Science, Engineering, or a related field
• Experience with local open-source models (e.g. Llama, Mistral, Mixtral) via Ollama, vLLM, or llama.cpp
• Fine-tuning with LoRA/QLoRA
• Familiarity with Docling or similar document parsing tools for RAG ingestion pipelines
• Familiarity with MLOps tooling (e.g. MLflow, Weights and Biases, SageMaker)

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