Senior Applied AI Engineer

Job Title: Senior Applied AI Engineer
Location: San Diego, CA
Contract length: 3 months
Schedule: Fulltime, 40 hrs/week
Pay: $120/hr to $132/hr, DOE

Job Overview:
The Senior Applied AI Engineer designs, builds, and deploys agentic AI solutions and other AI applications that improve business workflows across the enterprise. The role focuses on solutions that use approved tools and governed data, orchestrate multi-step work, and incorporate appropriate human oversight.
Working with business partners, Product Owners, Data Engineering, Security, Enterprise Architecture, and AI Governance, this role takes solutions from prototype to reliable production use in a regulated life-sciences environment. The engineer is also expected to provide technical direction and coordination for selected initiatives when needed.

Key Responsibilities:

• Solution Design & Delivery
  • Design and deliver agentic AI solutions, copilots, RAG applications, document intelligence, predictive models, and decision-support tools.
  • Build end-to-end AI pipelines and integrate approved models, governed enterprise data, APIs, tools, and workflow orchestration frameworks.
  • Partner with business and technical stakeholders to define requirements, success measures, acceptance criteria, and production-ready solutions.
• Engineering Practices
  • Apply strong software engineering, MLOps, and LLMOps practices for testing, deployment, monitoring, versioning, reliability, and cost management.
  • Create reusable components, prompts, evaluation assets, engineering standards, and technical guardrails that accelerate delivery and improve consistency.
• Technical Leadership
  • Lead defined technical workstreams as needed, facilitating design decisions and communicating technical options, risks, dependencies, and tradeoffs.
  • Coordinate technical delivery across internal teams and external partners, and provide code reviews, design feedback, troubleshooting support, and informal mentoring.
• Governance & Documentation
  • Implement security, privacy, responsible AI, data classification, access controls, traceability, and human approval safeguards.
  • Document solution design, data and model usage, evaluations, limitations, controls, and operational procedures.

Required Qualifications:

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.
• 5+ years of experience in software engineering, data engineering, machine learning engineering, or applied AI, including production delivery.
• Strong Python and software engineering skills, including modular design, testing, source control, CI/CD, APIs, and code review.
• Hands-on experience with LLM APIs, agent or workflow orchestration, tool integration, RAG, and enterprise data sources.
• Experience deploying secure AI solutions in Azure, AWS, or GCP and supporting them in production.
• Ability to guide technical workstreams, evaluate design tradeoffs, mentor peers, and communicate effectively with business and technical stakeholders.

Preferred Qualifications:

• Experience with production-grade agentic AI, including tool calling, state or memory, workflow execution, evaluation, and human approvals.
• Experience with Azure OpenAI, Azure AI Foundry, Copilot Studio, Semantic Kernel, LangChain, LlamaIndex, or similar platforms.
• Experience with vector search, MLOps or LLMOps platforms, and regulated or data-sensitive environments.
• Demonstrated success coordinating delivery across teams or partners and establishing reusable engineering practices.

What Success Looks Like:

• AI solutions deliver measurable business value and sustained user adoption.
• Solutions are secure, trusted, compliant, reliable, supportable, and cost-conscious.
• Reusable patterns accelerate delivery while maintaining appropriate governance.
• The engineer provides clear technical direction and effective coordination when leading selected initiatives.