Senior AI Engineer

Senior AI Engineer

We're looking for a Senior AI Engineer to build and scale production-grade AI systems that solve complex, real-world problems. This role is for engineers who are excited by modern AI application development—LLMs, retrieval systems, agents, and structured reasoning—and who thrive turning ambiguity into working software that ships.

This is a builder role. You'll own meaningful systems end-to-end, help move ideas from first draft to production, and iterate based on real usage and feedback. If you care deeply about shipping, learning quickly, and improving systems over time, this role is designed for you.

What You'll Do

• Design and build production AI applications using large language models (LLMs), retrieval systems, and agentic workflows
• Implement data extraction and context retrieval across structured and unstructured data sources
• Develop multi-step and tool-calling agent workflows that reason across data, documents, and systems
• Build and maintain data ingestion, normalization, and enrichment pipelines
• Integrate AI systems with application backends, APIs, and user-facing workflows
• Implement evaluation, monitoring, and feedback loops to measure accuracy, cost, latency, and reliability
• Collaborate closely with product, design, and domain experts to translate real workflows into AI-native solutions
• Contribute to architectural decisions with a focus on scalability, explainability, and long-term maintainability

Core Skills & Experience

• 5+ years of software engineering experience, with 3+ years building AI or ML systems in production
• Hands-on experience with LLMs including prompting, RAG, tool use, and orchestration
• Strong proficiency in TypeScript, React, Go, Python and modern AI frameworks
• Experience with vector or graph databases, embeddings, or semantic search
• Solid understanding of APIs, distributed systems, and cloud infrastructure
• Ability to balance speed, quality, cost, and correctness in production environments
• Strong debugging and problem-solving skills across data, model, and application layers

Builder Mentality (This Matters Here)

We are explicitly looking for builders.

By "builder," we don't mean job title or seniority, we mean an operating mode.

Builders:

• Bias toward systems that solve user needs, not perfect abstractions
• Move comfortably from ambiguity → first draft → iteration → production
• Optimize for learning velocity and customer impact, not theoretical completeness
• Are willing to build the entire arc of a system to surface real constraints early
• Treat quality as something you earn through iteration, not something you gate progress with
• Understand that the last 10–20% of a system—integration, edge cases, UX, usability, reliability—is where real work happens

In this role, being a builder means:

• Taking ownership of AI features from idea to production
• Being comfortable building an initial version quickly to learn what actually matters
• Collaborating openly, incorporating feedback fast, and iterating without ego
• Seeing incomplete systems as opportunities to learn—not reasons to stall
• Caring deeply about finishing and improving what you start

Preferred Experience (Domain-Flexible Specialties)

These are not requirements, but areas where deeper experience is a plus:

• Knowledge graph concepts: entities, relationships, schemas, ontologies
• Graph databases or technologies (e.g., Neo4j, Neptune, RDF) and graph querying
• Entity resolution, schema alignment, or knowledge fusion across multiple data sources
• Combining structured knowledge systems with LLMs
• Building AI systems in regulated or high-stakes domains where explainability matters
• Experience with financial, legal, healthcare, or enterprise data models
• Familiarity with evaluation frameworks, model monitoring, or AI quality metrics

What You'll Love

• Building real AI systems that make it into production and get used
• Working on hard, ambiguous problems where good solutions don't exist yet
• Seeing the direct impact of your work through customer outcomes and system performance
• A culture that values shipping, learning, and iteration over perfection
• Room to grow technically and take on deeper ownership as systems scale

About Us

We are an AI-first company, and we mean that literally.

AI is not a feature we bolt on. It's not a marketing layer. It's not a roadmap experiment. It is the foundation of how we design, build, and operate.

We are building systems where machines do what machines do best: pattern recognition, synthesis, analysis at scale. As well as what humans do what humans do best: judgment, context, trust, and accountability.

That means rethinking workflows from the ground up. Not "how do we add AI to this process?" but "how should this process exist in a machine-augmented world?"

We care deeply about shipping real systems that work in production. In regulated environments. With real customers. At scale.

If you're excited to help invent the next way software is built and deployed, and to do it alongside a team of deeply pragmatic, AI-obsessed builders, we'd love to talk.