Staff Software Engineer (AI/ML/ SaaS)

About the Position

Join ABBYY and be part of a team that celebrates your unique work style. With flexible work options, a supportive team, and rewards that reflect your value, you can focus on what matters most – driving your growth, while fueling ours.

Our commitment to respect, transparency, and simplicity means you can trust us to always choose to do the right thing.

As a trusted partner for purpose-built AI and intelligent automation, we solve highly complex problems for our enterprise customers and put their information to work to transform the way they do business. Over 10,000 customers trust ABBYY, including many Fortune 500 ones. You will work on further developing a portfolio already containing client names such as DHL, Johnson & Johnson, FDA, DMV, PwC, KeyBank, Spotify, and H&R BLOCK.

About the role:

We are looking for a Staff Software Engineer to help build and scale ABBYY’s AI platform. This role sits at the intersection of platform engineering, MLOps, and DevOps. You will own how AI services are built, deployed, observed, and evolved in production, with a strong focus on Kubernetes, cloud infrastructure, and ML lifecycle automation.

This is a hands-on technical leadership role. You will design systems, write production code, influence architecture, and mentor engineers.

Responsibilities

• Design and build scalable AI platform services using Python and microservice architectures
• Own DevOps and MLOps workflows including CI/CD, model deployment, versioning, and rollback
• Build and maintain Kubernetes-based platforms for AI workloads
• Work on data pipelines, dataset versioning, and auto-labeling workflows for model training
• Enable end-to-end ML lifecycle: data ingestion, training, evaluation, deployment, and monitoring
• Collaborate closely with ML researchers, product teams, and other platform engineers
• Drive best practices in software design, reliability, security, and observability
• Lead technical discussions, review designs, and mentor team members

Requirements

• 10+ years of experience in backend or platform engineering
• Strong proficiency in Python (or similar backend languages)
• Solid experience building microservices and distributed systems
• Hands-on expertise with Kubernetes in production environments
• Strong understanding of DevOps and MLOps principles
• Experience with data management for ML (datasets, labeling, pipelines)
• Cloud experience with Azure or strong willingness to adopt Azure quickly
• Ability to think at system level and still deliver hands-on

Nice to Have

• Experience building internal AI/ML platforms
• Familiarity with model serving frameworks and inference optimization
• Exposure to auto-labeling, weak supervision, or human-in-the-loop systems
• Experience in enterprise or B2B SaaS environments

We Offer

• Comprehensive medical, accidental, and life insurance
• Weekly wellness sessions to support physical and mental well-being
• Generous paid time off policy
• Remote and hybrid working options to fit all lifestyles
• Flexible hours across most of our teams
• Two paid volunteering days off every year
• Paid parental leave in all our locations

About the Company

ABBYY is a company with more than 35 years of experience in the technology market. Over 10,000 customers trust ABBYY, including many Fortune 500 ones, with names such as DHL, Johnson & Johnson, FDA, DMV, PwC, KeyBank, Spotify, and H&R BLOCK. We have modernized the capture market by creating the first low-code/no-code IDP platform. Our Machine Learning, Natural Language Processing, Computer Vision Technologies, and a marketplace built with AI, can transform any document in any process. Top Analyst firms recognize ABBYY's market leadership, including Gartner, Everest PEAK Matrix ® Assessment, ISG Intelligent Automation Lens, and NelsonHall, amongst others.

ABBYY is an Equal Employment Opportunity employer that values the strength that diversity brings to the workplace. To learn more about our commitment to Diversity and Inclusion, check out the careers section on our website.