Senior Software Engineer
- BROOKLYN, NY, United States
Technologies we love to use at Altana Languages: Python, PySpark Tools: Docker, Git, Kubernetes, Swagger/OpenAPI, AWS/Azure, MLFlow, Celery Datastores: Databricks and Delta Lakes This role is based in Brooklyn, NY, USA with hybrid work flexibility and candidates must be within commuting distance from our Williamsburg, Brooklyn office US Salary Range and Benefits $170,
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Job details
- Pay
- Technologies we love to use at Altana Languages: Python, PySpark Tools: Docker, Git, Kubernetes, Swagger/OpenAPI, AWS/Azure, MLFlow, Celery Datastores: Databricks and Delta Lakes This role is based in Brooklyn, NY, USA with hybrid work flexibility and candidates must be within commuting distance from our Williamsburg, Brooklyn office US Salary Range and Benefits $170,
- Posting language
- English
- Posted
Original job description
Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing.The Opportunity at Altana The Engineering team is responsible for building out the product for bringing this vision to life. We are creating a platform fundamentally driven by AI, which scales to a massive trove of data, and a diverse customer base; it is a complex system that will stretch engineering in many directions. Shipping products that customers actually adopt, not just products that ship, takes a particular kind of engineering practice. It means starting inside the customers workflow rather than at the ticket. It means treating every release as a hypothesis you can prove or disprove. It means reaching for AI as a primary building block, not a feature you bolt on at the end. And it means owning a product endtoend, from the first conversation through the telemetry six months later. As a Senior Engineer at Altana, thats the work and youll lead others doing it. Youll embed with product and design, get on calls with users, form hypotheses about where the real pain is, and lead a small team turning those hypotheses into shipped, adopted products. Youll measure your work in customer outcomes, not commits. You Will Spend real time with customers. Sit alongside them in their workflows, watch where they get stuck, and translate what you learn into product bets your team is willing to ship behind. Partner with the product team to decide what to build, not just how. Form hypotheses about customer value, design the smallest experiment that could prove them out, and learn fast. Push back on briefs that arent grounded in evidence. Take new product surfaces from 0 to 1. Pitch, prototype, ship, and drive adoption with real users. You are as fluent in did this land? as you are in is this maintainable? Build AInative by default. LLMs, agents, evals, retrieval, and modern AI tooling are firstclass building blocks in your stack, not boltons. You make principled choices about where AI changes the product equation and where it doesnt. Own endtoend outcomes. From the first customer conversation to telemetry on the dashboard six months later including the architecture and instrumentation choices that make that telemetry meaningful. Set the technical bar for your team. Review designs and code with a high standard for quality, simplicity, and customer impact, and a low tolerance for engineering work that can't be traced back to a customer outcome. Mentor engineers in customercentric, hypothesisdriven product development. Help them build the instincts to talk to users, run experiments, and tell when a feature is done because it's loved, not because the ticket is closed. Drive technical decisionmaking with a bias toward shipping. Choose practical, iterative designs that get a working version in front of customers fast, then evolve them as you learn. You Have Youve deployed production code and services to cloud-hosted environments. You have demonstrated experience delivering incremental releases from proof-of-concept to MVP to production. Self-starter with demonstrated experience working on large, complex problems. You care deeply about engineering excellence, clean code, and knowledge-sharing. You have strong written and verbal communication skills. Experience leading other engineers on complex projects. Nice to have, but not required Experience with Python Machine Learning toolsets (Numpy, Pandas, Dedupe). Experience with container technologies like Docker and Kubernetes. Technologies we love to use at Altana Languages: Python, PySpark Tools: Docker, Git, Kubernetes, Swagger/OpenAPI, AWS/Azure, MLFlow, Celery Datastores: Databricks and Delta Lakes This role is based in Brooklyn, NY, USA with hybrid work flexibility and candidates must be within commuting distance from our Williamsburg, Brooklyn office US Salary Range and Benefits $170,
More about this job
Skills
- Workflow
- Direct inward dialing
- Communication skills
- Python
- Machine learning
- NumPy
- Docker
- Kubernetes
- PySpark
- Git
- AWS
- Microsoft Azure
- Mlflow
- Databricks