Senior Software Engineer, AI-Native/First (New York)

LOCATION

This role starts hybrid, but quickly will transition to onsite in New York City. You need to be within commuting distance or willing to relocate before you start. We are not considering fully remote candidates for this position.

ABOUT PATTERNIQ

PatternIQ is an AI-powered consumer world model that simulates customer behavior at civilization scale. We’re building a continuously updating model of billions of people that predicts what they want, the content they’ll engage with, what they’ll buy, and how they will respond to any changes businesses want to simulate. This is critical infrastructure for advertising, commerce, pricing, product development, and eventually any AI system making decisions about consumers.

Our ML-driven programmatic ad network, InboxMatch, delivers unique ads to unique recipients inside a publisher's email campaigns. We replace the status-quo, one-size-fits-all static placement with hyper-personalized ads powered by a self-learning recommendation engine.

We're seed-stage and growing quickly. The culture is meritocratic and intense. We expect everyone to do their best work, raise the bar of the team they join, and act like owners. Debate is open and direct. We let data settle arguments.

THE ROLE

You'll design, build, test, deploy, and maintain scalable applications that millions of people will touch every month, and the infrastructure underneath them. You'll work across the full lifecycle: system architecture, backend services, integrations, performance, reliability, and security.

You'll also provide technical leadership. That means shaping engineering standards, reviewing code, sharing what works, and mentoring less experienced engineers.

We build AI-first. We expect you to be operating at the edge of what agentic development tools can do, and to bring the rest of the team with you.

WHAT YOU'LL DO

• Design, build, and ship production features across our TypeScript stack on AWS, working with Postgres, Redis, and event-driven architectures.
• Own services end-to-end, from schema design and implementation through deployment, monitoring, and incident response.
• Use CLI, IDE, and autonomous agent workflows as your default mode of building, not as a side experiment.
• Build and improve the internal patterns, prompts, and guardrails that make agent-assisted development reliable for the whole team.
• Improve and maintain CI/CD pipelines that keep us shipping with confidence multiple times a day.
• Collaborate with data and product to design and run experiments.
• Contribute to architectural decisions and trade-off discussions with direct, honest input. We attack ideas, not people.

WHAT WE'RE LOOKING FOR

AI-native/first practice, non-negotiable:

• Fluent across CLI, IDE, and autonomous agent workflows (Claude Code, Cursor, Codex, or equivalent) and understand fully about how they're changing the craft.
• Hands-on AI engineering with LLM-powered systems: evals, prompting, structured outputs, model behavior, or agent workflows.
• You push the boundary of what's possible with AI-assisted development rather than waiting for it to settle.

Engineering foundation:

• 3+ years of professional software engineering experience with a strong foundation in TypeScript and Node.js.
• Deep AWS experience: ECS or Lambda, RDS (Postgres), ElastiCache (Redis), SQS and SNS, CloudWatch. You've built and operated production systems here, not just deployed tutorials.
• Relational database fluency: schema design, query optimization, migrations, and operational awareness with Postgres.
• Enterprise B2B cloud software background. You've worked on systems where uptime, data integrity, and auditability actually matter.
• CI/CD ownership. You've built or meaningfully improved deployment pipelines and believe shipping safely and often is a core engineering responsibility.
• Monitoring and observability mindset. You instrument your code, set meaningful alerts, and investigate anomalies proactively.
• Comfort with ambiguity. We're iterating fast. Requirements shift. Context is incomplete. You thrive here because of the uncertainty, not despite it.