AI Solutions Engineer

Insight Global
Carlsbad, United States of America
4 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Carlsbad, United States of America

Tech stack

Artificial Intelligence
Python
Machine Learning
Software Engineering
Systems Integration
Enterprise Software Applications
Large Language Models
Multi-Agent Systems
Prompt Engineering
Model Validation
Generative AI
Backend
REST
Microservices

Job description

A large Life Sciences company based in San Diego, CA is seeking a Sr. AI Solutions Engineer to join their team for a short-term project based need. The Sr. AI Solutions Engineer designs, builds, and deploys AI-powered solutions that solve complex business challenges. This role combines expertise in software engineering, machine learning, large language models (LLMs), cloud platforms, and solution architecture to deliver scalable AI applications. The ideal candidate works closely with business stakeholders, data scientists, product managers, and engineering teams to translate business requirements into production-ready AI systems.

Requirements

6+ years of Software Engineering or ML/LLM Engineering experience with at least 3+ years focused on Artificial Intelligence and Generative AI solutions (Open AI preferred).

Strong hands-on development experience with Python and building production-grade backend services.

Experience designing and implementing Large Language Model (LLM) applications utilizing platforms such as OpenAI, Anthropic Claude, Gemini, or Llama.

Proven experience building RAG (Retrieval Augmented Generation) architectures and integrating vector databases.

Deep understanding of LangChain, AI orchestration frameworks, and agent-based architectures.

Experience building and consuming REST APIs, microservices, and event-driven integrations.

Strong knowledge of AI solution architecture, prompt engineering, model evaluation, and AI governance best practices.

Experience integrating AI capabilities into enterprise applications and workflows.

Experience designing scalable, secure, and maintainable enterprise applications.

Ability to communicate architecture decisions and AI strategies to both technical and business stakeholders.

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