Senior Software Engineer & AI Prompt Engineer (GenAI Full Stack)
Role details
Job location
Tech stack
Job description
The Senior Software Engineer & AI Prompt Engineer is responsible for the end-to-end design, development, and optimization of AI-powered software systems across Pacific Health Group. This role combines full-stack engineering with advanced prompt engineering to build scalable, production-grade Generative AI solutions, including LLM integrations, Retrieval-Augmented Generation (RAG) pipelines, and agentic AI systems. This position owns the full lifecycle of AI applications-from architecture and prompt design to deployment, monitoring, and continuous optimization-ensuring performance, reliability, and measurable operational impact. The role requires both hands-on technical execution and leadership in establishing AI engineering standards, best practices, and system scalability. Core Areas of Responsibility
- AI & Prompt Engineering
- Design, develop, and optimize prompts, chains, and workflows for LLM-based applications.
- Build and manage RAG pipelines, including ingestion, preprocessing, chunking, embeddings, indexing, retrieval, and evaluation.
- Architect and implement agentic AI systems, including multi-step reasoning, tool usage, orchestration, and multi-agent patterns.
- Establish prompt evaluation frameworks, benchmarking processes, and continuous improvement loops for quality, latency, and cost.
- Apply fine-tuning and domain adaptation techniques where necessary.
- Ensure responsible AI practices, including governance, safety, and reliability in production environments.
- Software Engineering & Full Stack Development
- Design and build scalable backend systems using Python (FastAPI or similar) and/or Java-based architectures.
- Develop modern front-end applications using React, Angular, or Vue frameworks.
- Build and maintain APIs, microservices, and integrations across internal and external systems.
- Ensure system performance, scalability, observability, and reliability across the stack.
- Contribute to architectural decisions and long-term technical roadmap development.
- Data & AI Infrastructure
- Design and manage data pipelines (ETL) to support AI workflows and model performance.
- Implement and maintain vector databases and embedding-based retrieval systems.
- Deploy, monitor, and optimize AI models in production environments.
- Optimize inference performance, scalability, and cost efficiency.
- Leverage cloud platforms (AWS, GCP, Azure) and AI services such as Vertex AI.
- Architecture & Technical Leadership
- Translate business requirements into scalable architectures, technical specifications, and delivery plans.
- Lead development efforts, including system design, code reviews, and engineering best practices.
- Mentor team members and promote a culture of engineering excellence and AI adoption.
- Collaborate cross-functionally with product, operations, and leadership teams to deliver impactful AI solutions.
- Evaluate emerging AI tools, frameworks, and technologies for practical implementation.
- Quality, Testing & Deployment
- Develop and implement testing strategies across application and AI layers, including unit, integration, regression, and performance testing.
- Maintain CI/CD pipelines and ensure production readiness of all systems.
- Monitor system performance, manage incidents, and drive continuous optimization.
- Ensure high standards of reliability, scalability, and consistency across releases.
- Compliance, Data Security & Governance (PHI, HIPAA, and AI Safety)
- Ensure all AI systems, data pipelines, and integrations comply with HIPAA and organizational data security standards.
- Implement safeguards for handling Protected Health Information (PHI), including encryption, access control, and secure transmission.
- Establish audit trails, monitoring systems, and governance frameworks for AI usage and data handling.
- Conduct risk assessments related to AI systems, data exposure, and model behavior.
- Collaborate with compliance and security teams to enforce best practices in data protection and AI governance.
Authority & Accountability
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Responsible for architecture, development, and performance of AI-powered systems across the organization.
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Authority to define and enforce engineering standards, AI practices, and system design decisions.
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Accountable for system reliability, scalability, security, and production readiness., Pacific Health Group maintains a structured, compliant, and secure hiring process in alignment with California labor laws. Employment offers are contingent upon successful completion of all required hiring steps, which may include:
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Submission of an internal or external application
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Recruiter screening
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Skills assessment (if applicable)
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Final interview with hiring leadership
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Formal verbal offer issued by an authorized representative
Important Notice: Any communication claiming to represent Pacific Health Group that does not follow this process should be considered unauthorized.
Requirements
- Strong systems thinker with high attention to detail.
- Ability to translate complex business problems into technical solutions.
- Bias toward automation, scalability, and performance optimization.
- High ownership mindset with proactive problem-solving capabilities.
- Comfortable operating in fast-paced, evolving technical environments.
Performance Indicators
- Successful deployment of scalable, production-grade AI systems.
- Measurable improvements in AI model performance, latency, and cost efficiency.
- High system uptime, reliability, and performance across applications.
- Increased adoption and impact of AI-driven features across the organization.
- Reduction in manual processes through intelligent automation and AI integration., * Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
- 5+ years of experience in software engineering or full-stack development.
- Hands-on experience with Generative AI technologies and LLMs (e.g., OpenAI, Anthropic, Gemini).
- Strong experience with prompt engineering, RAG pipelines, and agent-based AI systems.
- Proficiency in Python and JavaScript/TypeScript.
- Experience with modern front-end frameworks (React, Angular, or Vue).
- Experience with APIs, microservices architecture, and system integrations.
- Familiarity with vector databases and embedding-based systems.
- Experience with cloud platforms (AWS, GCP, or Azure).
- Strong foundation in data structures, algorithms, and system design., * Experience with model fine-tuning, training, and evaluation workflows.
- Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
- Experience with agent frameworks such as LangChain, LangGraph, or LlamaIndex.
- Knowledge of AI governance, risk, and compliance frameworks.
- Experience leading engineering teams or delivering client-facing AI solutions.
- Cloud or AI/ML certifications (AWS, Azure, or GCP).
Benefits & conditions
Time Off & Leave
- Paid Time Off (PTO)
- Paid Holidays
- Volunteer Time Off
- Bereavement Leave
Health & Wellness
- Comprehensive Medical Coverage
- Flexible Spending Accounts (FSAs) and wellness-related benefits
- Disability Insurance
- Employee Assistance Program (EAP)
Financial & Professional
- 401(k) Retirement Plan
- Role-based Stipends
- Professional Development and Continuing Education Support
Culture & Perks
- Employee Discounts
- Team Events and Offsites
- Career Growth and Advancement Opportunities