Tool Use / Function Calling Engineer.

The best engineers combine API design expertise with deep understanding of LLM reasoning patterns. They build self-healing tool chains that handle errors gracefully and validate outputs. Experience with schema design, type systems, and understanding how different models interpret function specifications sets top candidates apart.

Most companies want provider-agnostic expertise. Engineers should understand tool-use patterns across Anthropic, OpenAI, Google, and open-source models. Each has different function calling conventions and reliability characteristics. Building abstraction layers that work across providers is a highly valued and increasingly sought-after skill.

Princeton's cost of living multiplier is 1.15x the national average. The adjusted median Tool Use / Function Calling Engineer salary of $215,000 accounts for this. In practice, a Tool Use / Function Calling Engineer earning $215,000 in Princeton has roughly the same purchasing power as someone earning $186,957 in an average cost market.

Tool Use / Function Calling Engineer hiring in Princeton typically involves three to five rounds: a recruiter screen, a technical or skills assessment, one or two team interviews, and a final conversation with leadership. Companies in Princeton's Pharmaceuticals sector may add domain specific evaluations. The process usually takes two to four weeks. Prepare by researching the company and practicing with Orbyt's Interview Prep tool.

Remote work has compressed geographic salary premiums for Tool Use / Function Calling Engineers. Some Princeton employers offer location adjusted pay, while others maintain local rates to attract in office talent. In Princeton's moderate cost market, remote and local salaries are converging. The $160,000 to $281,000 range reflects both arrangements.

In Princeton, large enterprises typically pay Tool Use / Function Calling Engineers 10 to 20% more in base salary than small companies, but startups often compensate with equity that can exceed base salary value. Equity at AI platform companies is a significant compensation component. The $160,000 to $281,000 range reflects this entire spectrum.

Ask about equity structure, vesting schedule, annual bonus targets, 401(k) match, health insurance premiums, PTO policy, and remote flexibility. Equity at AI platform companies is a significant compensation component. In Princeton's market, these extras can add $53,750 or more on top of the base salary.