Job Description

Job Description

Job Description

Altimate AI, founded in 2022 in San Francisco, is revolutionizing enterprise data operations through the power of AI. Our mission is to alleviate the burden on overworked and understaffed enterprise data teams by providing innovative AI-driven solutions that automate and accelerate a wide range of data tasks. Our flagship product, DataPilot, offers advanced data automation capabilities, while our new DataMates technology brings the concept of agentic AI to data operations, acting as virtual teammates for data professionals. Our solutions seamlessly fit into existing tools like VSCode, Git, and Slack, performing tasks ranging from data documentation to performance optimization.

By leveraging a proprietary framework that combines multiple language models and a custom-built knowledge graph, we enable contextually aware AI agents that integrate seamlessly into existing workflows. Our solutions, including ambient AI for continuous monitoring and optimization, are designed to meet the growing demands of data operations, business intelligence, and analytics in an era of ever-increasing data volumes. Used by thousands of users across the world, and backed by prominent investors, we're positioned at the forefront of the AI-powered data engineering revolution. You can read more about us in a recently published venture beat article.

As a team, we are Silicon Valley veterans who previously created category-defining data and AI products loved by thousands of companies worldwide. We have experienced the journey of a small startup to IPO very closely. We have started on a similar journey again and are backed by prominent advisors and VC firms with multi-billion-dollar portfolios.

THE ROLE

We're hiring a Staff Product Engineer - someone who takes a feature from idea to production with full ownership. A builder, not a reviewer.

This role sits at the intersection of backend systems, product experience, and AI. You'll own complete product surfaces - APIs, data pipelines, and the LLM orchestration layer that ties it all together - and work directly with the founders to shape what gets built.

If you close the gap between what's built and what customers actually need, this is for you.

WHAT YOU'LL BUILD

• Own features end-to-end: scoping, architecture, implementation, and iteration based on user feedback

• Build backend systems powering AI-driven workflows — Python, FastAPI, PostgreSQL, Redis

• Ship LLM-native features: RAG pipelines, agentic workflows, prompt systems that operate on real data infrastructure

• Work on developer-facing surfaces: VS Code extensions, CLI tooling, dbt integrations, SQL intelligence

• Improve reliability and performance of production AI systems at scale

• Partner directly with founders and early customers to decide what to build next

WHAT WE'RE LOOKING FOR

Must have

• 8+ years building production systems

• Strong backend fundamentals - Python (or similar), APIs, distributed systems, databases

• LLM in production: RAG, agents, prompt pipelines

• Product instinct: you've pushed back on specs, rewritten requirements, and been right

• Startup DNA: you've set direction, not just executed it

Strong plus

• Experience with dbt, Airflow, Spark, or data platform tooling

• Familiarity with SQL parsing, ASTs, or data lineage

• TypeScript / React experience for full-stack ownership

• Former founder or early founding engineer

• Advanced AI Agent Architecture: Design and implement sophisticated multi-agent systems that can understand context, make decisions, and enable seamless collaboration between AI and human data professionals.

• Large-Scale RAG Systems: Build and optimize retrieval-augmented generation pipelines that can efficiently process and utilize enterprise-scale knowledge bases.

• Model Optimization & Deployment: Implement advanced techniques (LoRA, Prompt Tuning) to adapt off-the-shelf models for specific enterprise data tasks, ensuring faster, more accurate performance.

• Scalable AI Infrastructure: Develop and optimize cloud-native architectures (AWS, Kubernetes) for large-scale training, inference, and multi-agent orchestration.

• Enterprise Security & Compliance: Implement robust security measures for LLM applications, including data anonymization, prompt injection prevention, and compliance with enterprise security standards.

• Competitive salary and equity

  • Base Salary Range: $185,000 - $250,000 [influenced by your expertise, how the interview goes, and how well you match the role]

  • Equity: 0.05% - 0.5%

• Access to cutting-edge AI infrastructure and resources

• Team offsite and opportunities to attend and present at leading industry conferences (across the world)

• Learning budget for AI courses, books, and computing resources

• Dynamic and intellectually stimulating work environment with a team of talented engineers

• Opportunities to shape the direction of the company and leave a lasting impact

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