Data Scientist/AI ML Engineer

Position Overview:

We are seeking a Senior AI Engineer with deep LLM expertise to design and implement advanced

multi-agent AI systems, RAG pipelines, and AI infrastructure as part of an early engineering team.

Key Responsibilities:

• Build multi-agent AI systems orchestrating complex workflows and intelligent automation
• Develop advanced RAG pipelines with hybrid search capabilities using vector and keyword-based

retrieval

• Design prompt engineering frameworks ensuring consistent, high-quality outputs across multiple LLMs

such as Claude, GPT, and Qwen

• Create context management systems optimizing token usage and maintaining conversation coherence
• Fine-tune models specialized for domain-specific knowledge and terminology
• Implement vector search infrastructure leveraging OpenSearch for semantic similarity and knowledge

retrieval

• Develop LLM evaluation frameworks with automated quality metrics and regression testing
• Work on orchestration with LangChain for autonomous decision-making and task delegation
• Implement advanced prompt engineering including chain-of-thought and tree-of-thought reasoning
• Optimize context windows for long-form content generation and multi-turn conversations
• Build hybrid retrieval systems combining dense and sparse search with intelligent ranking
• Fine-tune models using PEFT techniques for domain adaptation
• Implement cost optimization through model routing, caching, and token management
• Collaborate with AI and backend teams to integrate AI systems into production environments
• Establish engineering standards for AI platform development

Required Skills:

• 3-5+ years building production AI systems
• 2+ years focused on LLM applications
• Production experience with Amazon Bedrock or similar managed LLM services
• Expert-level prompt engineering
• Context window and memory management for long conversations
• RAG development and vector search expertise using OpenSearch or similar databases
• Fine-tuning models such as Llama or Mistral using LoRA and QLoRA
• LangChain expertise for custom chains, agents, and tools development
• Proficiency in Python and TypeScript
• Experience with AWS ecosystem and managed services
• API design for LLM services with SSE streaming support
• Testing strategies for non-deterministic AI systems
• Security awareness including prompt injection prevention and data privacy

Preferred (Bonus) Skills:

• Experience with CrewAI or similar multi-agent frameworks
• Knowledge of supervisor, collaborative, and competitive agent patterns
• Familiarity with LangGraph for workflow orchestration
• Experience with Axolotl or similar fine-tuning frameworks
• Knowledge graph integration
• Experience with Pulumi for infrastructure as code
• Experience with microservices architecture and K8s
• Familiarity with NestJS and FastAPI frameworks
• Experience with PostgreSQL, Prisma ORM, and Redis caching
• Min 1 year experience in Agentic AI solutions like: Cursor AI or LangChain or AutoGen