Company Description Replicats is building AI-powered autonomous investment agents that bring institutional-grade portfolio management to everyone, starting with underserved retail investors in emerging markets. Our platform blends advanced quant models with conversational AI, making investing transparent, personalized and effortless. We’re looking for a Senior AI/LLM Engineer to lead the design, development, and optimization of our conversational layer—the “mouth and ears” of our investment agents. This role will be pivotal in turning our architecture vision into a real, engaging, and high-retention user experience. Responsibilities 1. LLM Subsystem Development Own end-to-end development of the conversational AI backend using Lang Chain, Open AI/Anthropic models, and retrieval-augmented generation (RAG). Design and implement long-term memory systems (vector DB + SQL hybrid) to persist user preferences, past interactions, and strategy history. Build multi-turn conversation state management to handle complex, ongoing user-agent dialogues. 2. Interaction & Personalization Create dynamic prompt construction pipelines incorporating real-time portfolio data, market sentiment, and user preferences. Implement risk profile adjustment flows with safe multi-step confirmation logic tied to portfolio rebalancing triggers. Develop feedback ingestion loops so conversational insights adjust the Quant Subsystem’s investment parameters. 3. Product Features & Proactivity Launch proactive agent features like daily market briefs, portfolio alerts, and contextual follow-ups. Integrate educational content with adaptive difficulty based on user engagement and knowledge level. 4. Quality & Evaluation Build an LLM response evaluation harness to track factual accuracy, compliance, and tone. Implement real-time telemetry and analytics to measure conversational performance and engagement. Requirements Technical Skills: 4+ years of experience in backend or AI engineering, with at least 2 years focused on LLM-based applications. Strong proficiency in Python and frameworks like Lang Chain or Llama Index. Experience with RAG pipelines, vector databases (Chromadb, Pinecone, Weaviate, Milvus, etc.), and Postgre SQL. Familiarity with conversational AI evaluation metrics and prompt engineering best practices. Knowledge of API integrations with financial/market data sources is a strong plus. Cloud experience such as AWS, Google Cloud Platform. Product & Collaboration Skills: Experience translating product roadmaps into executable AI feature builds. Ability to balance technical feasibility with user experience goals. Comfortable working cross-functionally with quant engineers, product managers, and frontend teams. Nice to Have Background in fintech, portfolio management, or trading systems. Experience with onchain data or blockchain-based execution. Familiarity with compliance requirements in financial conversational systems. What We Offer The chance to own and ship a core user-facing system in a cutting-edge AI + blockchain product. Fully remote, async-friendly work culture. Below market salary with huge equity upside.