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Principal AI Engineer

Role Overview

We are seeking a highly qualified Principal AI Engineer to own and architect our core intelligence and AI processing pipelines. You will be the technical authority on how we integrate, scale, and optimize artificial intelligence across our entire platform.This is not a prompt-jockey or wrapper-developer role. You will be responsible for architecting end-to-end, multi-modal solutions that push the boundaries of what is possible with applied AI. You will design agentic workflows, build complex user profiling systems to dynamically augment LLM context windows, and create proprietary intelligence layers that serve as competitive moat.

Key Responsibilities

● End-to-End AI Architecture: Design, build, and deploy production-grade AI systems, moving from idea inception to scalable AWS infrastructure. Bridge the gap between AI research and highly reliable software engineering.

● Agentic & Multi-Modal AI: Architect and implement autonomous, multi-agent systems that can reason, plan, use tools, and execute complex workflows across text, image, and data modalities.

● Custom Intelligence & Deep Context: Build sophisticated user profiling mechanisms and advanced RAG (Retrieval-Augmented Generation) pipelines to dynamically inject hyper-personalized context into foundational models.

● Advanced Prompt Engineering & Optimization: Lead the organization in

state-of-the-art prompt design, few-shot prompting, chain-of-thought reasoning, and structured output generation.

● Cost & Performance Optimization: Implement intelligent model routing, caching strategies, and token management to ruthlessly optimize inference costs, system latency,and overall API expenditure.

● Developer Productivity & Platform AI: Build internal tools, CI/CD pipelines for AI

(LLMOps), and automated evaluation frameworks to accelerate the development lifecycle and empower the broader engineering team to safely leverage AI.

● Cross-Functional Leadership: Serve as the technical visionary for AI , mentoring full-stack and front-end developers, and partnering with product leadership to identify novel ways AI can solve business problems.

Ideal Qualifications & Skills

● Experience: 8-10+ years of software engineering experience, with at least 3-5 years explicitly focused on applied Machine Learning, NLP, or Generative AI in production environments.

● Core Stack: Expert-level proficiency in Python and Node.js/TypeScript.

● AI & LLM Ecosystem: Deep hands-on experience with modern AI orchestration frameworks and integrating with frontier models (OpenAI, Anthropic, open-source equivalents).

● Data & Retrieval: Strong expertise in vector databases, embedding strategies, semantic search, and knowledge graph integration.

● Cloud & Infrastructure: Proven track record of designing scalable, distributed systems on AWS. Experience with containerization and serverless architectures.

● LLMOps & Evaluation: Experience building evaluation pipelines to measure AI accuracy, hallucination rates, and performance. Familiarity with AI observability and monitoring tools.

● Vision: A passion for building novel AI solutions and a pragmatic approach to balancing cutting-edge research with maintainable, production-ready code.