Lead Software Engineer

ABOUT SIGNA

Signa is a global enterprise SaaS platform that detects and removes illicit online product trade across social media, marketplaces and search engines. We collect forensic-grade evidence, coordinate the automatic removal of infringing content, verify product authenticity through user photo reports from messaging apps, and support investigations and enforcement with authorities to disrupt offline illicit networks.

We protect leading consumer goods, pharmaceutical, alcohol and FMCG brands across 10+ countries in the Americas, and we're expanding into India. Our North Star: the USD volume of abnormal products removed from the market. Our work protects consumers' health, brands' revenue and reputation, and gives authorities actionable intelligence.

THE ROLE

As Lead Software Engineer, you'll own the technical direction of a major area of our platform for several quarters. You'll design the systems, write the specifications, direct AI agents to build them, and review, test and harden what they produce. You'll also build the AI agents that run inside our product, and set the standards that let the whole team work AI-native.

This is a technical leadership role without formal people management.

WHAT YOU'LL DO

Technical direction

• Own the technical direction of a major platform area (data collection, evidence and claims, or data and AI) across several quarters

• Lead several cross-team initiatives in parallel and unblock delivery across squads

• Set architecture, reliability, security and AI quality standards that other squads adopt, written as RFCs and decision records

AI-native engineering

• Turn product needs into precise specifications, architecture and acceptance criteria that AI coding agents can execute

• Direct AI coding agents (Claude Code, Cursor, Codex or similar) to build features end to end, breaking work into tasks with the right context

• Review AI-generated code for correctness, security, performance and maintainability, and own the final call on what ships

• Build the guardrails that make AI-written code safe: automated tests, evals, CI quality gates and staged rollouts

• Define how the team works with AI: shared context files, prompt and agent conventions, review practices and playbooks

AI systems in our product

• Design and run LLM agents in production for detection, verification and evidence collection, including tool use and multi-agent orchestration

• Build evaluation frameworks, monitoring, drift detection and red-teaming for models and agents

• Integrate RAG, vector search and computer vision into product workflows

• Manage the cost and latency of AI in production, including model selection and token budgets

Platform, data and reliability

• Design event-driven, distributed systems on AWS that scale data collection across marketplaces and platforms

• Own streaming and ETL pipelines, and search and indexing foundations (OpenSearch patterns)

• Define SLOs and SLIs, lead incidents and postmortems, and own observability across metrics, logs and traces

• Apply security by design: threat modeling, secrets and key management, data access boundaries, and AI-specific risks such as prompt injection and data leakage

Raising the bar

• Mentor Leads and Senior developers to work AI-native, through design reviews, pairing and written feedback

• Act as the technical authority and escalation point for your domain

WHAT YOU BRING

• Daily, advanced use of AI coding agents in real production work. You can show how you structure specifications, context and reviews to get reliable output

• Strong systems design: distributed, event-driven architectures on AWS

• Deep code reading and judgment in Python and TypeScript. You review far more code than you type, and you catch what the agent missed

• LLM systems in production: agents, tool use, RAG, evaluations, guardrails and monitoring

• Data pipelines (streaming and ETL) and search and indexing at scale

• Reliability engineering: SLOs, incident leadership and observability

• Security architecture, including the risks introduced by AI systems and AI-generated code

• Infrastructure as code (CloudFormation, CDK or Terraform) and CI/CD with automated quality gates

• Clear technical writing: RFCs, specs and decision records others can act on

• Professional English, written and spoken

NICE TO HAVE

• Experience building or customizing agent frameworks, MCP servers or internal AI tooling

• Web data collection at scale: headless browsers, proxies and anti-bot strategies

• Computer vision or image similarity for product matching

• AWS certifications

• Background in trust and safety, fraud, brand protection or marketplace integrity

TOOLS YOU'LL WORK WITH

• AI: Claude, AI coding agents, LLM APIs, RAG, vector databases

• Languages: Python, TypeScript, Node.js

• Cloud and data: AWS (Lambda, ECS, S3, SQS, DynamoDB, RDS), OpenSearch

• Infrastructure and automation: Docker, IaC, CI/CD, n8n

WHAT WE OFFER

• Indefinite-term contract and 100% remote work

• 18 days of PTO per year, plus the public holidays of your country

• A clear technical career path on the Individual Contributor track, up to Principal

• Access to the latest AI tools, plus training and certifications

• Hard technical problems with AI at the core of the product, in a horizontal and autonomous team

WHAT WE VALUE

Mission-driven · Collaborative · Innovative · Accountable · Transparency · Autonomy · Continuous learning · Customer obsession

Learn more at www.signaip.com

Join us in making commerce safer and more trustworthy. Apply now 🚀