H
Senior Applied AI Engineer
Hydrogen UK Ltd
1 hour ago
Full-time
On-site
San Diego, California, United States
Title:
Senior Applied AI Engineer Pay:
$110.00-$130.00/hour Location:
San Diego, CA (Hybrid) Duration:
6-month contract Schedule:
Standard Office Hours
Job Summary 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.
Key Responsibilities AI Solution Design & Delivery
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.
Engineering & Development
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.
Technical Leadership
Lead technical workstreams 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.
Governance & Compliance
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.
Required Qualifications
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.
Preferred Qualifications
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
LangChain
LlamaIndex
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.
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Senior Applied AI Engineer Pay:
$110.00-$130.00/hour Location:
San Diego, CA (Hybrid) Duration:
6-month contract Schedule:
Standard Office Hours
Job Summary 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.
Key Responsibilities AI Solution Design & Delivery
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.
Engineering & Development
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.
Technical Leadership
Lead technical workstreams 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.
Governance & Compliance
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.
Required Qualifications
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.
Preferred Qualifications
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
LangChain
LlamaIndex
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.
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