AI Application Engineer
Job in
Santa Clara, Santa Clara County, California, 95053, USA
Listed on 2026-08-24
Listing for:
HMG AMERICA LLC
Full Time
position Listed on 2026-08-24
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Cloud Engineer - Software, Backend Developer
Job Description & How to Apply Below
- Build enterprise-grade AI applications that improve engineering, R&D, manufacturing, and knowledge management workflows.
- Accelerate adoption of Agentic AI across Applied Materials.
- Establish reusable AI platform components and frameworks.
- Reduce development effort through AI-assisted workflows and reusable services.
- Deploy production AI applications used by multiple business units.
- Deliver measurable productivity improvements.
- Create reusable RAG, agent, and orchestration frameworks.
- Improve knowledge discovery and decision support across engineering teams.
- Detailed Job Description & Key Responsibilities
- Design and build AI-powered applications using LLMs and foundation models.
- Develop RAG solutions leveraging enterprise knowledge sources.
- Build multi-agent systems for complex workflows.
- Design planning, reasoning, tool-calling, and workflow orchestration systems.
- Build autonomous and human-in-the-loop agent architectures.
- Fine-tune, evaluate, and optimize models.
- Implement prompt engineering and evaluation frameworks.
- Build API services for AI model consumption.
- Partner with R&D, product, and business stakeholders.
- Technical Stack, Frameworks & Programming Languages
- Python; SQL
- PyTorch;
Hugging Face Transformers;
Tensor Flow; MLflow
- Lang Graph;
Lang Chain;
Semantic Kernel;
Auto Gen
- FastAPI; REST APIs; gRPC (preferred)
- Cloud Environment
- ADLS Gen2
- Security, Compliance & Data Classification
- Understanding of enterprise security controls.
- Experience handling Internal and Confidential data.
- RBAC and identity management.
- Responsible AI implementation.
- Data governance frameworks.
- Model monitoring and auditability.
- PII protection and redaction.
- AI risk assessment and guardrails.
- Expected Deliverables & Success Criteria
- 1 2 production AI applications.
- Agent orchestration framework.
- Evaluation and observability dashboards.
- Reduced deployment time and development effort.
- Adoption across multiple teams.
- Success Metrics
- Productivity impact.
- Hallucination reduction. Required Years of Experience
- 5 8 years Software Engineering
- 3+ years AI/ML Engineering
- 1 2 years Generative AI
- 2+ years building production GenAI systems.
- Experience leading technical work streams.
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