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Sayari

Staff Software Engineer, Applied AI (Remote, US)

Posted 14 Days Ago
Easy Apply
Remote
Hiring Remotely in United States
200K-225K Annually
Expert/Leader
Easy Apply
Remote
Hiring Remotely in United States
200K-225K Annually
Expert/Leader
Lead an application squad to architect and implement scalable classical and AI-powered solutions, drive technical decisions for AI features, establish LLM evaluation frameworks and best practices, mentor engineers, perform deep code reviews, and collaborate with Product and Design to align development with the product roadmap.
The summary above was generated by AI
About Sayari: 

Sayari is a venture-backed and founder-led global corporate data provider and commercial intelligence platform that serves financial institutions, legal and advisory service providers, multinationals, journalists, and governments. Thousands of analysts and investigators in over 30 countries rely on our products to safely conduct cross-border trade, research front-page news stories, confidently enter new markets, and prevent financial crimes such as corruption and money laundering.

Our company culture is defined by a dedication to our mission of using open data to prevent illicit commercial and financial activity, a passion for finding novel approaches to complex problems, and an understanding that diverse perspectives create optimal outcomes. We embrace cross-team collaboration, encourage training and learning opportunities, and reward initiative and innovation. If you like working with supportive, high-performing, and curious teams, Sayari is the place for you.

POSITION DESCRIPTION

Sayari is looking for a Staff Software Engineer to help build our platform. An ideal candidate is a process-oriented self-starter with extensive experience in the software engineering world and interested in working on problems related to corporate transparency, anti money laundering, sanctions evasions, and combating financial fraud.If you are passionate about open source development and innovative technology, with a strong background in web development and engineering leadership, then we strongly encourage you to apply.

As Staff AI Engineer, you will lead implementation of one of the application team squads, overseeing that team's deliverables, architecting solutions, and ensuring code quality and maintainability, all while working closely with the product team and engineering leadership to ensure alignment with the product's roadmap.

JOB RESPONSIBILITIES
  • Architect classical and AI powered solutions that are robust, scalable, and thoroughly tested. Contribute directly to expanding the functionality and performance of our code base.
  • Collaborate with our Product and Design teams to evolve our platform roadmap, ensuring product goals are translated into tractable features that appropriately reflect our application's data model and capabilities. Identify capacity constraints to inform development sequencing and prioritization.
  • Lead technical architecture decisions for AI features, balancing research ambitions with production reliability
  • Establish evaluation frameworks and best practices for working with large language models in high-stakes, accuracy-critical domains
  • Act as a multiplier for the engineering team through hands-on mentoring, deep code reviews, and technical training on AI skillsets
SKILLS & EXPERIENCE

Required Skills & Experience: 

  • 10+ years of industry experience in software development, including experience as an IC and a mentor/lead.
  • Hands-on experience building production applications with LLMs (Prompt engineering, RAG, fine-tuning, or agentic workflows).
  • Deep understanding and proficiency with SQL and NoSQL databases, including Postgres, Cassandra, Elasticsearch, and/or Cypher-based graph databases
  • Proficiency in TypeScript and backend web development (REST APIs)
  • Experience managing software in cloud environments (GCP, AWS, or Azure).
  • Experience conducting code reviews and unit testing

Desired Skills & Experience:

  • Experience with Graph databases and query optimization for large-scale data.
  • Experience working on both front end and back end code bases
  • Experience with container orchestration via Kubernetes
  • Interest in data visualization, or how to visually present large, complex datasets
  • Exposure to batch processing frameworks like Spark

The target base salary for this position is $200,000-$225,000 plus annual bonus and equity. Final offer amounts are determined by multiple factors including location, local market variances, candidate experience and expertise, internal peer equity, and may vary from the amounts listed above.

Benefits: 
  • 100% fully paid medical, vision, and dental for employees and their dependents
  • Generous time off; we observe all US federal holidays, close our office for a winter break (12/24-12/31), in addition to granting 18 PTO days and 10 sick days
  • Outstanding compensation package; competitive commissions for revenue roles and bonuses for non-revenue positions
  • A strong commitment to diversity, equity, and inclusion
  • Eligibility to participate in additional benefits such as 401k match up to 5%, 100% paid life insurance (up to $100,000 coverage),, and parental leave
  • A collaborative and positive culture - your team will be as smart and driven as you
  • Limitless growth and learning opportunities
 
Sayari is an equal opportunity employer and strongly encourages diverse candidates to apply. We believe diversity and inclusion mean our team members should reflect the diversity of the United States. No employee or applicant will face discrimination or harassment based on race, color, ethnicity, religion, age, gender, gender identity or expression, sexual orientation, disability status, veteran status, genetics, or political affiliation. We strongly encourage applicants of all backgrounds to apply.
Pay Range
$200,000$225,000 USD

Top Skills

Agentic Workflows
AWS
Azure
Cassandra
Cypher
Elasticsearch
Fine-Tuning
GCP
Graph Databases
Kubernetes
Llms
NoSQL
Postgres
Prompt Engineering
Rag
Rest Apis
Spark
SQL
Typescript

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