Senior Applied AI Engineer

Title: Senior Applied AI Engineer
Pay: $110.00-$130.00/hour
Location: San Diego, CA (Hybrid)
Duration: 6-month contract
Schedule: Standard Office Hours

Our client is seeking a Senior Applied AI Engineer to design, build, and deploy enterprise AI solutions that improve business workflows through agentic AI, large language models (LLMs), and intelligent automation. This role is responsible for taking AI solutions from proof of concept through production deployment while ensuring security, governance, and compliance in a regulated environment. The position partners closely with cross-functional stakeholders to deliver scalable, production-ready AI applications and provide technical leadership across key initiatives.

• Design, develop, and deploy agentic AI solutions, copilots, retrieval-augmented generation (RAG) applications, document intelligence solutions, predictive models, and decision-support tools.
• Build end-to-end AI pipelines integrating approved models, enterprise data sources, APIs, workflow orchestration frameworks, and automation tools.
• Collaborate with business stakeholders, Product Owners, Data Engineering, Security, Enterprise Architecture, and AI Governance teams to define requirements, success metrics, and production-ready solutions.
• Translate prototypes into scalable, reliable, enterprise-grade applications.

• Apply software engineering best practices, including testing, CI/CD, version control, monitoring, deployment, and cost optimization.
• Implement MLOps and LLMOps processes to support production AI applications.
• Develop reusable prompts, engineering components, evaluation frameworks, technical standards, and guardrails to improve development efficiency and consistency.
• Ensure AI solutions are maintainable, scalable, and reliable.

• Lead technical work streams for assigned initiatives.
• Evaluate design alternatives, communicate technical recommendations, and identify risks, dependencies, and tradeoffs.
• Coordinate delivery across internal teams and external partners.
• Perform code reviews, provide design guidance, troubleshoot technical issues, and mentor engineering team members.

• Implement AI governance standards, including security, privacy, responsible AI, access controls, data classification, traceability, and human approval workflows.
• Document solution architecture, model usage, data flows, evaluations, operational procedures, limitations, and governance controls.
• Ensure compliance with enterprise policies and regulated industry requirements.

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field (or equivalent practical experience).
• 5+ years of experience in software engineering, machine learning engineering, data engineering, or applied AI with production deployment experience.
• Strong Python development skills and experience with software engineering best practices, including:
  • Modular application design
  • Automated testing
  • Source control
  • CI/CD pipelines
  • REST APIs
  • Code reviews
• Hands-on experience with:
  • Large Language Model (LLM) APIs
  • Agentic AI and workflow orchestration
  • Retrieval-Augmented Generation (RAG)
  • Enterprise data integration
  • Tool integration frameworks
• Experience deploying and supporting secure AI solutions in Azure, AWS, or Google Cloud Platform (GCP).
• Ability to lead technical initiatives, evaluate architectural tradeoffs, mentor peers, and communicate effectively with both technical and business stakeholders.

• Experience developing production-grade agentic AI solutions featuring:
  • Tool calling
  • Workflow execution
  • State management and memory
  • Human approval workflows
  • Evaluation frameworks
• Experience with platforms and frameworks such as:
  • Azure OpenAI
  • Azure AI Foundry
  • Copilot Studio
  • Semantic Kernel
  • Lang Chain
  • Llama Index
• Experience with vector databases/search technologies and MLOps or LLMOps platforms.
• Experience delivering AI solutions within regulated or highly governed environments.
• Demonstrated success establishing reusable engineering standards and coordinating cross-functional technical delivery.