Our direct client is looking for
Senior
Applied AI Engineer
to join the team on a full time direct hire.
This will be working 3 days week on site in
**San Diego, CA 92130
- Local candidates only that is able to work 3 days onsite per week.
**Applicants must be authorized to work for ANY employer in the U.S. Must have permanent authorization to work in the U.S.
The client is unable to sponsor or take over sponsorship of an employment Visa at this time.**
Position Details
- Senior Applied AI Engineer
- Full Time – Direct Hire position.
- Either Location: San Diego, CA 92130
- Hybrid, 3 days week onsite.
- Salary $120k - $150k + Bonus, equity and great Benefits
- Travel may be required up to 5% of your time.
The
Senior
Applied AI Engineer
builds and deploys AI solutions that directly support business workflows across Commercial, Regulatory, Quality, Finance, Operations, and Corporate functions. This role focuses on
turning real business problems into working AI applications
—including copilots, retrieval-augmented generation (RAG) solutions, document generation, automation agents, predictive models and decision-support tools.
The Senior Applied AI Engineer works closely with business SMEs, Data Engineering, and the AI Governance team to ensure solutions are
secure, compliant, explainable, and production-ready
in a regulated life-sciences environment.
**SKILLS:
Required Qualifications**
- Bachelor’s degree in Computer Science, Engineering, Data Science, or related field
- 3–5 years of experience in software engineering, data engineering, or applied AI engineering
- Strong proficiency in Python is required
- Experience building and deploying applications using LLM APIs
- Hands-on experience with ML frameworks (PyTorch, TensorFlow, scikit-learn)
- Experience deploying AI solutions in cloud environments (Azure, AWS, or GCP)
- Strong understanding of data engineering fundamentals , APIs, and distributed systems
Preferred Qualifications
- Experience with RAG architectures, vector databases, and semantic search
- Exposure to Azure OpenAI, Copilot Studio, LangChain, LlamaIndex, or similar frameworks
- Familiarity with MLOps platforms (MLflow, SageMaker, Azure ML, Databricks)
- Experience in regulated or data-sensitive environments (pharma, healthcare, finance)
- Familiarity with AI governance, responsible AI, model explainability, and data classification
- Experience building **enterprise copilots or agentic AI solutions
Key Skills**
- Applied AI/ML & Prompt Engineering
- Generative AI & LLM Integration
- Enterprise Data Integration
- API & Cloud Application Development
- Security-aware Engineering
- Business Problem Solving & Systems Thinking
- Stakeholder Communication & Collaboration
**RESPONSIBILITIES:
Applied AI Solution Development**
- Build AI applications such as copilots, search assistants, document intelligence/generation, workflow automation agents, predictive models and decision-support tools.
- Implement RAG pipelines using enterprise data sources (SharePoint, data lake, document repositories, research systems, etc.)
- Build and maintain end-to-end AI pipelines : data ingestion, feature engineering, model training, evaluation, deployment, and monitoring
- Integrate LLMs via APIs and platforms (Azure OpenAI, OpenAI, Anthropic, AWS Bedrock) into business workflows
- Develop prompt engineering, grounding, and evaluation frameworks to improve accuracy and reliability
Enterprise AI Enablement
- Translate business use cases (e.g., medical affairs, regulatory, commercial, finance) into working AI prototypes and production apps
- Collaborate with Data Scientists to translate models into scalable production systems
- Collaborate with Product Owners and SMEs to refine requirements and success metrics
- Build reusable **AI components, prompt libraries, and solution patterns
Production & Platform Engineering**
- Deploy and maintain AI solutions using cloud platforms and modern APIs
- Implement basic MLOps and LLMOps : versioning, monitoring, logging, performance tracking
- Integrate with identity, access control, and data-security platforms (RBAC, Purview, etc.)
- Implement logging, observability, performance tracking, and cost optimization for AI workloads
- Ensure reliability, scalability, and security of AI systems in production environments
Governance & Compliance
- Ensure AI solutions follow data classification, privacy, and AI governance policies
- Support documentation for model usage, data sources, and risk assessments
- Implement guardrails to prevent data leakage, hallucinations, and misuse
Must be able to pass and clear background check and Drug Test prior to starting.
The client Will Require 2 professional Work References to be completed prior to starting.
**Applicants must be authorized to work for ANY employer in the U.S. Must have permanent authorization to work in the U.S.
The client is unable to sponsor or take over sponsorship of an employment Visa at this time.**
If you are interested, please send me your updated
Word Resume
, along with your direct phone number and email.