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

AI ML Engineer