Senior Software Engineer (AI)

TL;DR

Sr. Software Engineer - Applied AI (Cybersecurity): Building and shipping LLM-powered systems that reduce toil, accelerate remediation, and improve decision-making in operations contexts with an accent on evaluation frameworks and retrieval-augmented pipelines. Focus on translating ambiguous operational problems into AI-first solutions and implementing guardrails and safety systems.

Location: This role can be based out of Sunnyvale/Silicon Valley Metro, Redmond/Seattle Metro, Austin Metro or New York City Metro and will likely include 1-3 days in-office per week on average (NYC and Austin office are in development and/or expanding, so workers here will remain fully remote for likely 18-24 months)

Salary: $140,000 - $215,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off.

Company

hirify.global protects the people, processes and technologies that drive modern organizations, redefining modern security with the world’s most advanced AI-native platform.

What you will do

• Build and ship LLM-powered systems that reduce toil, accelerate remediation, and improve decision-making in operations contexts.
• Design and maintain evaluation frameworks: hallucination tests, regression harnesses, benchmarks, and quality gates for safe rollout.
• Develop retrieval-augmented pipelines (RAG) and data strategies for grounding on logs, telemetry, runbooks, and system metadata.
• Engineer AI copilots and natural-language interfaces to interact with operational data and workflows.
• Implement guardrails and safety systems: prompt injection defenses, PII filtering, constrained decoding, and model observability.
• Build developer-facing SDKs and APIs in Python/Go; intuitive UIs in JavaScript/React for human-in-the-loop workflows.

Requirements

• Proven experience shipping LLM-based systems into production with measurable impact.
• Expertise in evaluation and testing of LLMs (benchmarks, hallucination/regression tests, grounding metrics).
• Strong programming skills in Python and Go.
• Hands-on experience with LLM orchestration frameworks: LangChain, LangGraph, MCP, agent frameworks, or equivalent.
• Deep understanding of RAG pipelines: embeddings, retrieval quality metrics, re-ranking, and grounding precision/recall.
• Ability to translate ambiguous operational problems into AI-first solutions with clear KPIs.

Nice to have

• Experience with fine-tuning/adapters (LoRA, QLoRA, continual learning) and safety tuning.
• Exposure to inference optimization and serving, partnering with platform teams on latency, scaling, and resilience.
• Experience building AI copilots/assistants for engineers.

Culture & Benefits

• Market leader in compensation and equity awards.
• Comprehensive physical and mental wellness programs.
• Competitive vacation and holidays for recharge.
• Paid parental and adoption leaves.
• Professional development opportunities for all employees regardless of level or role.
• Great Place to Work Certified™ across the globe.