Artificial Intelligence Engineer

Title: Senior Applied AI Engineer

Location: Palo Alto, CA (3 days on site)

Duration: Perm Hire

Salary: $130K-250K

JOB DESCRIPTION

Insight Global is looking for Senior Applied AI Engineers to join an automotive customer in the electric vehicle space. As an AI Engineer, you will contribute across the stack, from data pipelines and retrieval to prompt/agent logic, evaluation/guardrails, and serving. You will collaborate closely with partners across Operations, Product, Sales, Customer Service, Finance, HR, and other internal teams to understand needs and deliver practical solutions that create tangible business value. You will develop responsibly, partnering with governance stakeholders on privacy, security, compliance, and safety. Responsibilities Build features and services across the AI stack: orchestration, retrieval/grounding, prompt/agent logic, evaluation/guardrails, serving, and observability. Implement robust data processing and integration pipelines to enable high-quality AI applications and analytics. Contribute to design docs, code reviews, testing, and operational playbooks to ensure reliability, maintainability, and resilience. Partner with product and business stakeholders to define requirements, iterate quickly, and measure outcomes using clear success metrics. Instrument telemetry and evaluation to monitor quality, safety, latency, and cost; improve performance based on data. Follow responsible AI practices for security, privacy, compliance, and safety in collaboration with governance teams. Participate in on-call and incident response rotations as appropriate; drive post-incident improvements. Share learnings via demos and documentation; contribute to AI literacy and enablement across the org.

REQUIRED SKILLS AND EXPERIENCE

• BS/MS in Computer Science or a related field, or equivalent experience.
• Practical software engineering experience building backend services, APIs, or data-intensive applications; strong foundations in algorithms, data structures, and systems.
• Exposure to or hands-on experience with LLM application concepts such as retrieval, grounding, prompt/agent design, function/tool use, evaluation, safety/guardrails, and cost/latency optimization.
• Proficiency with modern software delivery practices (version control, CI/CD, testing, observability); familiarity with cloud-native services and containerization.
• Ability to collaborate with product and business partners; strong written and verbal communication skills.
• Bias to ship, learn, and iterate; comfortable working in fast-evolving technology areas with incomplete information.
• Demonstrated ownership of services or platform components, end-to-end delivery of cross-service initiatives, and contributions to reliability/SLOs and operational excellence.