Staff Software Engineer

Altana; New York (NY); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

Competitive base salary

Learning & development support

Health benefits (global)

Paid time off

Equity program

Parental leave

Job summary

Altana is building an AI-native platform with a focus on delivering products customers actually adopt. As Staff Engineer, you will lead engineers embedded with product and design, engaging with customers, formulating hypotheses, and turning them into shipped, adopted solutions.

You will own the end-to-end technical architecture, telemetry, and instrumentation, ensuring designs and code deliver measurable customer value.

Qualifications

• Self-starter with demonstrated experience working on large, complex problems.
• Experience deploying production code and services to cloud-hosted environments.
• Strong written and verbal communication skills.
• Experience leading other engineers on complex projects.
• Care about engineering excellence, clean code, and knowledge-sharing.
• Experience delivering incremental releases from proof-of-concept to MVP to production.
• Experience with Python Machine Learning toolsets (Numpy, Pandas, Dedupe).
• Experience with container technologies like Docker and Kubernetes.

Responsibilities

• Lead a small team turning hypotheses into shipped, adopted products.
• Embed with product and design, interact with users, and translate learnings into product bets.
• Measure work in customer outcomes, not commits.
• Spend time with customers in their workflows to observe pain points.
• Drive technical decision-making with a bias toward shipping and iterative design.
• Set the technical bar for the team with high standards for quality and traceability.

Skills

Python

PySpark

LLMs

Agents

Retrieval

ML tooling

Docker

Git

Kubernetes

Swagger/OpenAPI

AWS/Azure

MLFlow

Celery

Databricks

Delta Lakes

Tools

Docker

Git

Kubernetes

Swagger/OpenAPI

AWS

Azure

MLFlow

Celery

Databricks

Delta Lakes

Job description

• 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 customer’s 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 end‑to‑end, from the first conversation through the telemetry six months later
• As a Staff Engineer at Altana, that’s the work and you’ll lead others doing it
• You’ll 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
• You’ll measure your work in customer outcomes, not commits
• 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 aren’t 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 AI‑native by default. LLMs, agents, evals, retrieval, and modern AI tooling are first‑class building blocks in your stack, not bolt‑ons. You make principled choices about where AI changes the product equation and where it doesn’t
• Own end‑to‑end 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 customer‑centric, hypothesis‑driven 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 decision‑making 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
• 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

Benefits

• Competitive base salary: We offer competitive base salaries to recognize the incredible work our employees do.
• Learning & development: We support your development through regular performance check-ins and offer financial support for Learning and Development initiatives.
• Health benefits: We offer full global benefits, including a 100% employer-paid plan and tax-advantaged HSA and FSA options in the US.
• Paid time off: We provide a generous PTO policy, including paid sick time, to support your well-being in and out of the office.
• Equity program: We instill ownership by offering competitive new hire equity grants, plus the opportunity to gain more equity along the way.
• Parental leave: We offer up to 26 weeks of fully paid parental leave to support you and your family.

You’ve deployed production code and services to cloud-hosted environmentsSelf-starter with demonstrated experience working on large, complex problemsYou have strong written and verbal communication skillsExperience leading other engineers on complex projectsYou care deeply about engineering excellence, clean code, and knowledge-sharingYou have demonstrated experience delivering incremental releases from proof-of-concept to MVP to productionExperience with Python Machine Learning toolsets (Numpy, Pandas, Dedupe)Experience with container technologies like Docker and Kubernetes