# AI / LLM Engineer

## About the Role

We are seeking a highly skilled and forward-thinking **AI / LLM Engineer** to help lead the development of AI-powered product features, intelligent workflows, and internal automation systems. This role is ideal for an engineer who understands how to design, build, evaluate, and improve large language model applications in practical business environments.

The AI / LLM Engineer will work on features that may include job matching, applicant scoring, resume analysis, conversational workflows, classification, ranking, summarization, document extraction, recommendations, and AI-assisted internal automation. This person will work across model selection, prompt design, data pipelines, retrieval-augmented generation, structured outputs, evaluation methods, production monitoring, and AI system architecture.

This role requires both strong engineering ability and a practical understanding of how AI systems behave in real-world use. The ideal candidate can translate business goals into reliable AI workflows, build systems that produce consistent and useful outputs, and help ensure AI-powered features are accurate, explainable, scalable, and maintainable.

## Key Responsibilities

* Design and implement LLM-powered product features and internal AI workflows across company platforms and tools.
* Build AI systems for job matching, candidate evaluation, applicant scoring, resume analysis, document extraction, recommendations, summarization, classification, ranking, and conversational workflows.
* Develop prompt chains, tool-calling workflows, agentic processes, structured output pipelines, and model-assisted decision systems.
* Create retrieval-augmented generation systems using embeddings, vector databases, hybrid search, semantic search, metadata filtering, and ranking strategies.
* Work with AI APIs, open-source models, model orchestration frameworks, and AI development tools to build reliable and scalable features.
* Design systems that classify, rank, score, summarize, extract, or match data based on complex business rules and structured requirements.
* Build data pipelines that prepare, clean, transform, enrich, and organize information for AI processing and model-driven workflows.
* Develop structured output processes using JSON schemas, validation rules, retry logic, fallback prompts, and deterministic formatting requirements.
* Create evaluation methods to test AI accuracy, consistency, fairness, hallucination risk, relevance, reliability, and output quality.
* Monitor AI performance in production and identify issues related to drift, inconsistent outputs, edge cases, model limitations, or degraded quality.
* Collaborate with backend developers to integrate AI features into production systems, APIs, databases, and user-facing applications.
* Work with product leadership to understand business needs and translate them into practical AI system designs.
* Create fallback logic, guardrails, confidence thresholds, validation workflows, and human-review processes where appropriate.
* Document AI architecture, prompts, workflows, evaluation criteria, implementation choices, and known limitations.
* Support experimentation with different models, prompting strategies, retrieval methods, scoring approaches, and evaluation techniques.
* Stay current with LLM tooling, model capabilities, AI safety practices, retrieval methods, orchestration frameworks, and emerging AI engineering patterns.

## Qualifications

* Strong experience building AI-powered applications, LLM workflows, machine learning systems, or intelligent automation tools.
* Hands-on experience working with large language models, AI APIs, prompt engineering, structured outputs, and model-assisted workflows.
* Experience designing and implementing retrieval-augmented generation systems, including embeddings, vector databases, semantic search, and relevance ranking.
* Strong programming skills, preferably in Python, JavaScript, TypeScript, or another language commonly used for AI and backend development.
* Experience working with APIs, databases, data pipelines, JSON, structured data, and backend integrations.
* Understanding of prompt design, prompt chaining, tool calling, agent workflows, output validation, and model orchestration.
* Ability to create evaluation methods for accuracy, consistency, hallucination risk, relevance, fairness, and output quality.
* Experience building classification, ranking, matching, scoring, summarization, extraction, or recommendation systems.
* Understanding of how to monitor AI systems in production and troubleshoot model output issues.
* Ability to translate business requirements into technical AI solutions that are practical, measurable, and maintainable.
* Strong problem-solving skills and the ability to work through ambiguity in fast-moving product environments.
* Clear communication skills and the ability to explain AI system behavior, risks, tradeoffs, and design decisions to technical and non-technical stakeholders.

## Preferred Qualifications

* Experience with job matching, applicant scoring, resume parsing, recruiting technology, HR technology, or talent marketplace platforms.
* Experience with OpenAI, Anthropic, Google Gemini, Hugging Face, or similar AI model providers and ecosystems.
* Familiarity with vector databases such as Pinecone, Weaviate, Chroma, Milvus, Qdrant, pgvector, or similar tools.
* Experience with orchestration or AI workflow frameworks such as LangChain, LlamaIndex, Semantic Kernel, Haystack, CrewAI, AutoGen, n8n, or similar platforms.
* Experience designing production workflows that use structured JSON outputs, function calling, tool use, schema validation, and retry handling.
* Familiarity with model evaluation, test sets, synthetic data generation, scoring rubrics, benchmark workflows, and quality monitoring.
* Understanding of AI safety concepts, including hallucination mitigation, fairness, bias testing, privacy, data handling, and guardrail design.
* Experience with cloud platforms, containerized services, serverless workflows, or scalable backend infrastructure.
* Familiarity with SQL, NoSQL, search indexes, document stores, and data enrichment pipelines.
* Experience working in a startup, SaaS company, product-led team, or fast-paced engineering environment.

## Ideal Candidate Profile

The ideal candidate is a practical AI engineer who can move beyond demos and prototypes into production-ready systems. This person understands that successful AI features require more than a prompt. They require good data, clear rules, strong evaluation, thoughtful error handling, reliable integrations, and ongoing monitoring.

This person should be comfortable experimenting with models and workflows while also building systems that are structured, documented, testable, and maintainable. They should be able to work with product leaders to clarify business goals, with developers to deploy AI features, and with stakeholders to explain how AI outputs are generated, evaluated, and improved.

The right candidate will bring curiosity, technical depth, and strong judgment. They should enjoy solving complex problems involving language, data, ranking, scoring, automation, and user-facing AI experiences.

## Work Environment

This role will involve close collaboration with product leadership, backend developers, designers, and business stakeholders. The AI / LLM Engineer should be comfortable working in a remote or hybrid environment, participating in product planning discussions, reviewing workflows with technical teams, and iterating quickly based on testing, user feedback, and business priorities.

The environment is fast-paced and product-focused. The successful candidate should be able to balance experimentation with practical implementation and should be comfortable helping shape AI features from concept through deployment and ongoing improvement.

## Compensation and Benefits

Compensation will be based on experience, qualifications, and overall fit for the role. Benefits may include:

* Competitive salary
* Full-time employment
* Remote work flexibility
* Paid time off
* Professional development opportunities
* Opportunity to work on modern AI-powered product features
* Collaborative and innovative work environment
* Opportunity to help shape the company’s AI architecture and product direction

## Equal Opportunity Statement

We are an equal opportunity employer and welcome applicants from all backgrounds. Employment decisions are based on qualifications, experience, skills, and business needs. We are committed to maintaining a respectful, inclusive, and collaborative work environment.