Senior Scientist, AI & Data Infrastructure

Kingdom • New York, NY

16h • $132,500 - $160,000 • Onsite

About The Position

At Kingdom, we’ve pioneered Superculture® ingredients: an entirely new class of clinically-validated postbiotics that target the root causes of unmet pet health needs. We’re actively selling Superculture® Pet Oral and Superculture® Pet Immune to pet food and supplement brands, and will be launching our first Superculture ingredient for humans later this year. We're looking for a high-performing Senior Scientist, AI & Data Infrastructure, to join our small but mighty team. This is an AI-native science role: you'll own the computational backbone of Kingdom's research (the microbial genomics and AI-compatible data infrastructure that every wet-lab program depends on) and ship custom and integrated LLM tooling to automate and accelerate our work. We want a PhD-level computational biologist (or related area) who applies rigorous scientific judgment to genomic analysis, biobank strategy, and statistical methods, and is equally excited to build the systems that let everyone move faster. Fundamentally, this is a science role, with success measured by the integrity of our data, the insights our data infrastructure unlocks, and the AI tooling we deploy across our scientific platform. This is a full-time, in-person role at our headquarters in Brooklyn, NY. We founded Kingdom in 2019 to cultivate healthier living with natural microbes, and have raised $35M+ in venture funding from top investors. Less than a year in market, our ingredients are already powering dozens of products from leading pet brands, with overwhelmingly positive customer reception. 1 out of 3 product launches using our ingredients have earned a #1 New Release on Amazon, and 9 out of 10 of our customers are launching additional products with us. Our core technical edge is our scientific platform, which spans ingredient discovery, clinical trials, and manufacturing scale-up.

Requirements

• PhD (or equivalent depth) in computational biology, bioinformatics, microbial genomics, or a related quantitative life-sciences field; ~1-3 years post-PhD
• Domain depth in microbial genomics: whole-genome sequencing, 16S/ITS amplicon analysis, dereplication, taxonomy, and genomic safety annotation
• Strong knowledge of statistics and quantitative methods
• Advanced coding literacy: expert-level Python or R, proficiency with SQL, fluency with containerization for reproducible pipelines, comfort building tools that interact with third-party APIs, and strong code-quality practices (version control, testing, code review)
• Experience designing and maintaining bio-data infrastructure: proficiency modeling complex interrelated entities and comfort establishing and communicating an ontology
• AI-native: daily Claude Code or equivalent use, prompt fluency, comfort rebuilding research cadence around agentic tools, with experience building tooling around your own research
• High agency: self-starter who identifies pain points, proposes a plan and solution, and drives their own learning
• Builder mentality: comfortable with building a first version of a tool fast, and iterating to improve
• Bias to actionable output: instinct to package findings into something concrete that unblocks decisions and moves the next step forward
• Clear and effective written and verbal communication

Responsibilities

• Build and own Kingdom’s AI-compatible scientific data infrastructure: Build AI-compatible data infrastructure for Kingdom that captures, stores, and analyzes data across a variety of modalities
• Develop and apply statistical and computational methods to power biological insights and support wet-lab workflows, including experimental design, metric development and validation, and method onboarding, powered with new AI/agentic tools
• Maintain the integrity of the strain database backend: tube tracking, naming conventions, and audits of our physical inventory and pipeline data to identify anomalies
• Model complex, interrelated scientific entities (samples, experiments, runs, results, physical inventory) into a coherent schema and ontology the team can work in
• Scope, build, and ship the data processing, analysis, and metrics that give new assays clear, validated benchmarks
• Own genomic analyses and biobank strategy: Run computational genomic safety analyses and author the supporting reports that underpin our regulatory and customer-facing safety documentation
• Maintain the whole-genome sequencing pipeline: assembly of incoming sequencing data, linkage of genomes to strain records, and curation of best-available assemblies for downstream use
• Own and operate the strain dereplication pipeline, advancing isolated colonies from primary 16S/ITS screening through unique-strain identification and entry into the biobank
• Design and curate screening plates for downstream functional assays, including layout, strain selection, and verification of taxonomy and safety annotations

Benefits

• Equity stock options
• 100% fully-covered, best-in-class medical, vision, and dental insurance for yourself (and 95% for your spouse/family)
• Generous and flexible PTO
• 13 company-wide holidays
• Full commuter coverage
• Fully stocked kitchen with fruits, snacks, and beverages
• Weekly team lunches
• 12-weeks fully-paid parental leave
• 401k program with minimal fees

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree