compLogoAI EngineerCompany: INCEDO INCHybridSan Diego, CA, USA
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Job Title: AI Engineer
Location: San Diego, CA
Duration: Full-time
Senior
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 Responsibilities
AI 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