Data Platform Engineer

Data Based Development Systems; United States; On-site; USD 170,000 - 260,000; Full time

Job summary

Data Based Development Systems seeks a senior technical leader to integrate production-grade AI, ML and data capabilities, blending hands-on software engineering with system-level design for scalable, cloud-based solutions.

You will collaborate with cross-functional stakeholders, mentor engineers, and drive end-to-end capabilities such as LLMs, MLOps, GenOps, and ML-augmented engineering, ensuring design, implementation, and operation meet quality and CI/CD standards.

Qualifications

• Requires a university degree or equivalent with 12+ years of relevant experience.
• Advanced degree in a related field with 10+ years of experience preferred.
• Experience with data science and ML and lifecycle in software development.

Responsibilities

• Collaborate with leadership, PMs, and stakeholders to advance data capabilities.
• Act as system integrator for APIs, SDKs, and automation to deploy AI/ML in production.
• Maintain high-level and low-level views of systems and coordinate with SMEs.
• Design, test, and deploy production-grade software with CI/CD, observability, and maintainability.
• Mentor engineers and contribute to documentation and support activities.
• Lead multi-disciplinary teams toward senior or lead roles.

Skills

Data science

Machine learning

Python

SDLC

Cloud computing

Leadership

Education

University degree or equivalent

Advanced degree in related field

Tools

REST APIs

SQL

Node

Testing libraries

Job description

This role is a senior technical leadership position responsible for integrating and delivering production-grade AI, machine learning, and data capabilities. The position combines hands-on software engineering with system-level design, leading end-to-end development of scalable, cloud-based solutions that leverage LLMs, MLOps, and automation. Working closely with cross-functional stakeholders, the role balances near-term delivery with long-term strategy while mentoring engineers and promoting strong engineering best practices.

What You Will Do:

• Collaborate with technical leadership, product managers, program/project managers, and business stakeholders to support the team as we bring advanced data capabilities.
• Be the system integrator for APIs, SDKs, and other automation activities: lead multi-disciplinary efforts to bring advanced AI/ML capabilities through production software and cloud engineering, including generative AI, AIOps, GenOps, MLOps, and ML-augmented engineering. This includes ensuring that capabilities are designed, implemented, maintained, observed, and supported from end-to-end.
• Maintain both high level and low-level views of technical systems and coordinate with teams and subject matter experts from other disciplines to realize successful realization.
• Design, write, test, and deploy production quality software capabilities that are maintainable, automated (CI/CD), scalable, observable, organized, and readable. Ensure best practices are maintained, including quality and CI/CD automation.
• Advise technical support and building of user documentation
• Mentor early and mid-career team members, supporting their ascension to senior and lead roles.

Qualifications You Must Have:

Typically requires a University Degree or equivalent experience and minimum 12 years prior relevant experience, or an Advanced Degree in a related field and minimum 10 years’ experience

• 5+ years of experience with data science and machine learning.
• 5+ years of experience with the Software Development Life Cycle and software application / product development, including Python and the Python scientific stack.

Qualifications We Prefer:

A flexible and patient mindset, interested in working on a variety of multi-disciplinary challenges with varying stakeholders, partners, domains, and toolsets.

• Relevant experience with cloud computing platforms (AWS and/or Azure.)
• Organizational skills for knowledge, documentation, and data management
• Other helpful experience: SQL, Node, REST APIs, testing libraries.
• Experience building products that use Large Language Models (LLMs) and LLM APIs.
• Technical leadership experience, such as being the engineering lead for a program, product, or large project.
• Experience as part of a multi-disciplinary team