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Salary: USD 170,000 - 200,000 / annual
Altana is building an AI-powered product network for trusted trade, helping governments and businesses create a more resilient and secure global economy. The Engineering team is responsible for shipping products that customers actually adopt, not just products that ship.
As a Senior Engineer at Altana, you will lead a small team in building AI-native products end-to-end. Your work will span from initial customer conversations through shipped features and telemetry analysis six months later. You'll embed closely with product and design teams, spend time with customers to understand their workflows, and translate those insights into product hypotheses your team ships behind.
Key responsibilities include:
- Spending real time with customers to identify pain points and translate learnings into product bets
- Partnering with product to decide what to build, not just how to build it; forming and testing hypotheses about customer value
- Taking new product surfaces from 0 to 1: pitching, prototyping, shipping, and driving adoption
- Building AI-native by default, treating LLMs, agents, evals, and retrieval as first-class building blocks rather than bolt-ons
- Owning end-to-end outcomes, including architecture and instrumentation choices that make telemetry meaningful
- Setting the technical bar for your team through design and code review, with high standards for quality, simplicity, and customer impact
- Mentoring engineers in customer-centric, hypothesis-driven product development
- Driving technical decision-making with a bias toward shipping practical, iterative designs that get working versions in front of customers fast
The role emphasizes measuring work in customer outcomes rather than commits, and treating every release as a hypothesis to prove or disprove.
Requirements:
- Deployed production code and services to cloud-hosted environments
- Demonstrated experience delivering incremental releases from proof-of-concept to MVP to production
- Self-starter with demonstrated experience working on large, complex problems
- Deep care for engineering excellence, clean code, and knowledge-sharing
- Strong written and verbal communication skills
- Experience leading other engineers on complex projects
Nice to have:
- Experience with Python Machine Learning toolsets (Numpy, Pandas, Dedupe)
- Experience with container technologies like Docker and Kubernetes
Technologies used: Python, PySpark, Docker, Git, Kubernetes, Swagger/OpenAPI, AWS/Azure, MLFlow, Celery, Databricks, Delta Lakes.
