AI Engineer
by Qode
in
Job role overview
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Date posted
May 4, 2026
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Hiring location
California
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Qualification
Bachelor's Degree
Description
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
work mode
On-site
Interested in this job?
20 days left to apply