AI Engineer

Job Title: AI Engineer Location: San Diego, CA Duration: Full-timeSenior Location: We are seeking a Senior AI Engineer to design, build, and scale enterprise-grade AI platforms leveraging frontier Large Language Models (LLMs). This role sits at the intersection of AI engineering, platform architecture, and applied GenAI, with a strong emphasis on productionization in regulated environments (financial services, wealth, capital markets).You will play a key role in operationalizing AI at scale, building reusable capabilities, and enabling secure, governed adoption of LLM-powered solutions across the enterprise.

Key ResponsibilitiesAI Platform Engineering

* Design and build scalable AI platforms supporting LLMs, RAG pipelines, and multi-model orchestration

* Develop reusable frameworks for prompt management, model routing, evaluation, and monitoring

* Implement LLMOps / MLOps pipelines for continuous integration, deployment, and lifecycle management

* Architect API-first AI services for enterprise-wide consumption

Frontier LLM Integration

* Integrate and optimize models from providers like OpenAI, Anthropic, Google DeepMind, and open-source ecosystems

* Build multi-model strategies (closed + open source) for performance, cost, and governance

* Implement advanced techniques:

* Retrieval-Augmented Generation (RAG)

* Tool use / agents

* Fine-tuning and embeddings

* Context optimization and memory systems

Enterprise AI & Governance

* Design systems aligned with security, compliance, and data privacy requirements

* Implement guardrails, auditability, and explainability in AI workflows

* Enable safe AI deployment in distributed environments (e.g., advisor desktops, hybrid cloud)

Applied AI Solutions

* Build AI-driven use cases such as:

* Intelligent document processing (e.g., wealth plans, research docs)

* Advisor copilots and decision support systems

* Knowledge assistants and enterprise search

* Partner with business teams to translate use cases into scalable AI solutions

Performance & Evaluation

* Develop evaluation frameworks for accuracy, hallucination detection, and model performance

* Optimize latency, throughput, and cost for production deployments

* Establish benchmarking and observability standards

Required Qualifications

* 7-12+ years in software engineering, with 3+ years in AI/ML engineering or GenAI

* Strong proficiency in:

* Python, APIs, microservices architecture

* LLM frameworks (LangChain, LlamaIndex, etc.)

* Hands-on experience with:

* RAG pipelines, vector databases (Pinecone, FAISS, etc.)

* Cloud platforms (AWS, Azure, GCP)

* Deep understanding of transformer models, LLM architecture, prompt engineering, and context handling

* Experience building production-grade AI systems (not just POCs)

Preferred Qualifications

* Experience in financial services / wealth / capital markets

* Familiarity with regulated AI deployments (compliance, DLP, governance)

* Exposure to agentic AI systems and autonomous workflows

* Experience with fine-tuning / LoRA / model optimization

Knowledge of data engineering pipelines and real-time architectures