Sr. AI Engineer

Description

The company makes precision timing devices using MEMS technology, an alternative to quartz that offers better accuracy, smaller size and stronger resilience in harsh conditions. Its parts are used in more than 400 applications, including AI datacenters, automated driving, industrial and humanoid robots, wearables and IoT, and more than 4 billion devices have shipped.

The team needs a hands-on senior engineer to build, launch and run AI applications and agents across the business. You will turn valuable business problems into secure, scalable tools that connect large language models to company data, knowledge and core systems.

You will be involved in the whole lifecycle, from quick prototypes through evaluation, deployment, monitoring and continuous improvement. The focus is on measurable results, responsible AI and reusable engineering patterns.

Responsibilities

• Take LLM-based applications and agentic workflows from prototype to reliable production.
• Connect AI systems securely to business systems, data platforms, APIs, knowledge bases and workflow tools using approved integration patterns.
• Build retrieval-augmented generation pipelines covering ingestion, chunking, indexing, metadata, access controls, retrieval and grounding.
• Create evaluation datasets and automated tests for accuracy, completeness, safety, latency, reliability and cost, adding human review where useful.
• Set up CI/CD, observability, prompt and model versioning, incident response, and ongoing monitoring of performance and cost for AI services.
• Develop shared services and patterns for model access, orchestration, secure connectors, memory, tool use, auditability and policy enforcement.
• Protect confidential data and intellectual property through least-privilege access, data handling controls, logging, red-teaming and company policies.
• Work with product owners, business functions, Business Applications, Data, Security and IT to define outcomes, set priorities and fit solutions into existing workflows.
• Track adoption and outcome metrics, measure time, quality or cycle-time gains, and refine work based on evidence.
• Review designs and code, document architectures and runbooks, mentor engineers, and keep up with new models, frameworks and enterprise AI patterns.

Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science or a related field.
• 7+ years of software engineering experience, including 3+ years building AI/ML or generative AI solutions.
• Proven record of shipping LLM-based applications or agents to production, not just prototypes.
• Strong Python skills and experience building production services, APIs, and distributed or cloud-native applications.
• Working knowledge of prompting, RAG, tool and 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 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 such as ERP, CRM, collaboration, ticketing and data systems.
• Strong written and verbal communication, able to turn business needs into technical designs and explain trade-offs clearly.
• English proficiency is required to communicate, collaborate and carry out the job in a professional business setting.
• Preferred: a master's degree.
• Preferred: hands-on experience with the Microsoft AI ecosystem, such as Azure AI Foundry, Azure OpenAI, Microsoft 365 Copilot, GitHub Copilot, Copilot Studio, Microsoft Graph and Power Platform.
• Preferred: experience with one or more orchestration frameworks and model providers, keeping the architecture provider-independent where practical.
• Preferred: experience building governed enterprise agent marketplaces, reusable agent components or model gateways.
• Preferred: experience with MLOps or LLMOps, automated evaluation, red-teaming, tracing and AI cost management.
• Preferred: experience applying AI to Sales, Finance, Operations, HR, Engineering or Customer Support workflows.
• Preferred: semiconductor, electronics or manufacturing industry experience.
• Desired: a hands-on builder who works comfortably across architecture, code, integrations, evaluation, deployment and operations.
• Desired: starts with the problem and expected outcome, then picks the simplest effective technology.
• Desired: moves quickly, ships in iterations, and owns reliability and value after launch.
• Desired: treats data protection, responsible AI, testing and observability as core engineering work.
• Desired: builds trust with technical and non-technical partners and works well across functions.
• Desired: keeps up with a fast-changing field without chasing technology that has no clear use case.

Conditions

Base salary range is $124,920 to $171,770 USD.

You do not need to meet every requirement to apply, and the company welcomes diverse experiences and career paths.

Benefits

• Quarterly bonus tied to achieving innovation goals, in addition to base salary.
• Equity grants.
• 401k plan.
• Health and wellness coverage including medical, dental, vision and life insurance.
• Parental leave, legal services and time-off plans.