Sr. AI Engineer

SiTime Corporation

Santa Clara (CA)

On-site

USD 125,000 - 172,000

Full time

4 days ago

Be an early applicant

Application generator

Turn this role into an interview — a resume and cover letter built around what this employer wants.

Get past ATS filters

Benefits offered by this job

401(k) plan

Medical, dental, vision, and life insu

Parental leave

Legal services

Time-off plans

Quarterly bonus

Equity grants

Job summary

SiTime Corporation in Santa Clara, CA seeks a hands-on Sr. AI Engineer to design, build, deploy, and operate production-grade AI applications and agents that connect large language models with SiTime data and systems.

The role emphasizes shipping LLM-based applications to production, building secure integrations, and advancing enterprise AI patterns with a focus on responsible AI and cost-aware optimization.

Qualifications

Bachelor’s degree in CS, Engineering, Data Science, or related field.
],
job_responsibilities_description

Responsibilities

Build production AI applications and agentic workflows.

Skills

Python

LLM patterns

CI/CD

Data pipelines

Vector search

Security controls

Enterprise integration

English fluency

Education

Bachelor's degree

Master's degree preferred

Tools

Azure AI Foundry

Azure OpenAI

Copilot Studio

Power Platform

GitHub Copilot

Microsoft Graph

CI/CD tooling

Job description

SiTime Corporation is seeking a hands‑on Sr. AI Engineer to design, build, deploy, and operate production‑grade AI applications and agents that connect large language models with SiTime data and systems.

Responsibilities

Build production AI applications by designing and implementing LLM-powered applications and agentic workflows that progress from prototype to reliable deployment.
Develop enterprise agents and integrations by connecting AI solutions securely to business systems, data platforms, APIs, knowledge bases, and workflow tools using approved integration patterns.
Implement retrieval and knowledge solutions, including RAG pipelines with ingestion, chunking, indexing, metadata, access controls, retrieval, and grounding.
Engineer for quality and trust through evaluation datasets and automated tests covering accuracy, completeness, safety, latency, reliability, and cost; add human review where appropriate.
Own deployment and operations by establishing CI/CD, observability, prompt and model versioning, incident response, and ongoing performance and cost monitoring.
Build reusable platform components including shared services and patterns for model access, orchestration, secure connectors, memory, tool use, auditability, and policy enforcement.
Apply responsible AI and security controls to protect confidential information and intellectual property using least privilege access, data handling controls, logging, red‑teaming, and adherence to SiTime policies.
Partner with business and technology teams to define outcomes, prioritize use cases, and deliver solutions that fit existing workflows across product, business functions, Business Applications, Data, Security, and IT.
Measure business value by instrumenting adoption and outcome metrics, quantifying time, quality, or cycle-time improvements, and iterating based on evidence.
Advance engineering practices through design and code reviews, documentation of architectures and runbooks, mentorship, and staying current on models, frameworks, and enterprise AI patterns.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (master’s degree preferred).
7+ years of software engineering experience, including 3+ years building AI/ML or generative AI solutions.
Experience shipping LLM-based applications or agents to production, not only prototypes.
Strong Python skills with experience building production services, APIs, and distributed or cloud-native applications.
Working knowledge of LLM application patterns including prompting, RAG, tool/function calling, structured outputs, agent orchestration, and model evaluation.
Experience with vector search, embeddings, document processing, data pipelines, and enterprise knowledge retrieval.
Experience with cloud AI services and modern engineering practices such as containers, CI/CD, infrastructure automation, testing, monitoring, and source control.
Understanding of identity, authorization, secrets management, data privacy, secure API design, and responsible AI controls.
Ability to integrate with enterprise platforms including ERP, CRM, collaboration, ticketing, and data systems.
Excellent written and verbal communication skills to translate business needs into technical designs and explain trade-offs clearly.
English proficiency required to communicate, collaborate, and perform job responsibilities in a professional business environment.

Technologies

Python
CI/CD, CI, CD
Containers
ERP, CRM
Azure AI Foundry, Azure OpenAI
Microsoft 365 Copilot, Github Copilot, Copilot Studio
Microsoft Graph, Power Platform
Vector search, embeddings, retrieval-augmented generation (RAG)
LLM, LLMOps, MLOps
E-Verify

Preferred Qualifications

Hands‑on experience with the Microsoft AI ecosystem including Azure AI Foundry, Azure OpenAI, Microsoft 365 Copilot, Github Copilot, Copilot Studio, Microsoft Graph, and Power Platform.
Experience with orchestration frameworks and model providers while maintaining provider‑independent architecture where practical.
Experience building governed enterprise agent marketplaces, reusable agent components, or model gateways.
Experience with MLOps/LLMOps, automated evaluation, red‑teaming, tracing, and AI cost management.
Experience applying AI to enterprise workflows in Sales, Finance, Operations, HR, Engineering, or Customer Support.
Semiconductor, electronics, or manufacturing industry experience.

Benefits