AI Product Engineer

About the role

We're looking for someone to fill a unique seat on the product team. A builder who sits at the intersection of data science, AI, and product development. The person in this role must operate with high agency: take fuzzy, early-stage concepts and turn them into working features end to end, collaborating closely with product leadership and domain experts throughout the process. We need someone who can help us scale that way of working across the organization.

Responsibilities

• Work closely with our intelligence and product teams to create, build, and deliver novel, innovative capabilities powered by AI and machine learning.
• Apply machine learning, NLP/text analytics, and generative AI (including large language models) to real problems in the threat intelligence domain.
• Prototype rapidly, turning half-formed ideas into working demos that sharpen the team's thinking.
• Build and maintain production services on AWS, writing clean Python and JavaScript across the stack.
• Stay current on emerging AI/ML techniques and proactively surface "how could we use this?" opportunities relevant to Seerist's domain.
• Collaborate closely with product, engineering, and solutions teams to ensure what gets built actually solves customer problems.

Requirements

• Mindset & Working Style:
  • Agency. You don't wait for a perfectly scoped ticket. You hear a fuzzy idea, ask the right questions, and start moving.
  • Collaborative challenge. You push back thoughtfully when something doesn't make sense, and you welcome the same in return. The process of building is a conversation, not a handoff.
  • Intellectual curiosity. You're always learning, reading papers, trying new tools, exploring adjacent domains, and you naturally connect what you're learning to what the team is building.
  • Communication. You can explain complex technical concepts clearly to non-technical stakeholders, write well, and keep people in the loop without being asked.
• Technical Skills:
  • A strong foundation in machine learning and data science — you've trained models, evaluated them rigorously, and put them into production.
  • Hands-on experience with generative AI and large language models (fine-tuning, prompt engineering, RAG architectures, evaluation).
  • Proficiency in Python for data/ML work and JavaScript for web development.
  • Experience with text analytics and NLP, classification, extraction, summarization, entity resolution.
  • Comfortable building and deploying on Amazon Web Services (Lambda, SageMaker, ECS, S3, etc.).
  • Able to work across the stack, from data pipelines to APIs to front-end interfaces.
• Background:
  • A bachelor's degree in a relevant field (computer science, data science, mathematics, or similar).
  • Exceptional written and verbal communication skills, demonstrated through academic and professional experience.
  • 3+ years of professional experience in a role combining data science, ML engineering, or AI product development.
  • Experience shipping ML/AI features in a product context (not just notebooks and research).

Qualifications

• Exceptional written and verbal communication skills, demonstrated through academic and professional experience.
• 3+ years of professional experience in a role combining data science, ML engineering, or AI product development.
• Experience shipping ML/AI features in a product context (not just notebooks and research).
• Nice to have:
• Familiarity with the threat intelligence, geopolitical risk, or security domain.
• Experience working in a startup or growth-stage environment where scope is fluid.
• Exposure to event-driven architectures or real-time data processing.

Skills

• Strong foundation in machine learning and data science — you've trained models, evaluated them rigorously, and put them into production.
• Hands-on experience with generative AI and large language models (fine-tuning, prompt engineering, RAG architectures, evaluation).
• Proficiency in Python for data/ML work and JavaScript for web development.
• Experience with text analytics and NLP, classification, extraction, summarization, entity resolution.
• Comfortable building and deploying on Amazon Web Services (Lambda, SageMaker, ECS, S3, etc.).
• Able to work across the stack, from data pipelines to APIs to front-end interfaces.

Benefits

Opportunity to work in a fast-moving, high-growth SaaS company
Competitive salary, bonus plan, 401(k) matching, and long term incentives
Comprehensive benefits including health, dental, vision, and life plans
Strong, results oriented culture
Remote and office-based work (3+ days in Reston office each week)
Paid Time Off
Paid Parental Leave (16 Weeks Primary, 4 Weeks Secondary)
Tuition Reimbursement
Professional Development Stipend

Pay

TBD

Schedule

Varies