Senior AI Engineer - Applied AI & Data Validation
SAP · Sofia
- We help the world run better
- At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.
What you'll build
At SAP, we enable you to bring out your best. Our culture is built on collaboration and a shared passion to help the world run better. SAP offers a highly collaborative, caring team environment with a strong focus on learning and development, recognition for individual contributions, and flexible benefit options.
SAP is looking for an AI Engineer who can turn business problems into practical AI solutions and help ensure the data behind those solutions is accurate, relevant, and ready for use. This is a hands-on role for someone who enjoys building AI applications while also stepping in as an ad-hoc data scientist to assess source quality, validate assumptions, and improve data readiness across the delivery lifecycle.
You will work with cross-functional teams to move high-value AI use cases from discovery to production, balancing speed, technical quality, and real business impact.
As an AI Engineer, you will design, build, validate, and operationalize AI solutions that support business and operational teams. You will work across the full delivery lifecycle, from early requirements and prototyping through production readiness and post-launch improvement.
Key responsibilities include:
- Build AI and agent-based solutions that solve real business problems and can be deployed in production environments.
- Translate business needs into technical designs, data requirements, evaluation approaches, and delivery plans.
- Act as an ad-hoc data scientist to assess whether data sources are relevant, complete, trustworthy, and fit for the intended use case.
- Explore, clean, profile, and validate data from enterprise systems to improve model quality and reduce delivery risk.
- Design and implement prototypes, pipelines, model workflows, orchestration logic, and integration components.
- Partner with business stakeholders, product owners, engineers, and data owners to define success metrics and align on outcomes.
- Support discovery workshops and early solution design by bringing a strong perspective on technical feasibility and data readiness.
- Define and execute testing and evaluation approaches for AI solutions, including data validation, output quality, and operational performance.
- Prepare solutions for production by contributing documentation, monitoring requirements, release evidence, and handover materials.
- Analyze usage, feedback, and impact after launch, then turn those insights into recommendations for improvement, scaling, or redesign.
- Share reusable patterns, lessons learned, and engineering best practices to strengthen overall AI delivery capability across teams.
What you bring
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical field.
- Strong hands-on experience in AI engineering, machine learning, data science, software engineering, or a similar role.
- Proven ability to take AI or ML solutions from idea to implementation, including data validation, prototyping, testing, deployment, and operational support.
- Strong programming skills in Python and solid SQL experience.
- Experience working with enterprise data, including profiling, quality assessment, transformation, and validation.
- Good understanding of machine learning methods, statistical analysis, model evaluation, and modern AI application patterns.
- Experience building or supporting AI applications, intelligent workflows, copilots, or agent-based solutions is a strong advantage.
- Ability to work in ambiguous environments, structure problems quickly, and make sound technical decisions with incomplete information.
- Strong communication skills and the ability to explain technical concepts, trade-offs, and data limitations to non-technical audiences.
- Experience working in cross-functional teams that include business stakeholders, engineers, and governance or compliance partners.
- Familiarity with human-centered design, discovery workshops, or design-thinking approaches is a plus.
- Experience with production readiness topics such as monitoring, documentation, runbooks, security alignment, and lifecycle support is a plus.
Where you belong
You will join a team focused on identifying, building, and scaling practical AI use cases that deliver measurable value. The team works closely with business stakeholders, architects, engineers, and operations partners to bring AI solutions into production quickly and responsibly.
This environment is ideal for someone who enjoys combining technical depth with business impact, moving from experimentation to deployment, and working across both AI engineering and data validation responsibilities.
- Bring out your best
- SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your