Description
We are looking for a Senior Data and AI Solutions Engineer to partner with engineering teams and transform data, BI, automation, and agentic AI into measurable engineering productivity gains.
As a Senior Data and AI Solutions Engineer, you will work closely with engineers, managers, and cross-functional teams to understand complex engineering domains, identify bottlenecks, and build practical solutions that improve decision-making, execution speed, and operational quality.
Your responsibilities will include developing and delivering production-grade tools, automated workflows, and agentic AI solutions from concept through deployment. You will run fast, high-quality proof-of-concepts on emerging AI and agentic technologies, and productize successful ones.
You will also implement data flywheels that continuously improve quality through telemetry, benchmarking, automated evaluation, and structured feedback loops. You will collaborate and contribute ideas and code to Product Engineering's evolving data infrastructure.
In addition, you will improve data quality, integrity, governance, metric definitions, and usability across engineering domains. You will train and enable engineers, managers, and stakeholders to use data, BI, and AI tools effectively.
To succeed in this role, you will need a B.Sc or M.Sc in Computer Science, or related field, or equivalent experience. You will also require 12+ years of proven experience building and deploying production software, data products, internal tools, or engineering productivity platforms and 2+ years of experience building AI-enabled or agentic systems, including tools & skills, RAG pipelines, persistent memory, and evaluation infrastructure.
You will need hands-on development experience with Python, full-stack software development, SQL and NoSQL databases, cloud environments, and internal tool development. You will also need extensive experience utilizing coding agents for development.
A proactive, high-agency builder who deciphers complex domains to deliver pragmatic, production-grade AI and data solutions that drive measurable engineering productivity is essential. An adaptable expert who masters the intersection of software engineering and agentic AI, taking full ownership of the lifecycle from messy data debugging to cross-functional leadership is also required.
Excellent collaboration skills, with the ability to influence cross-functional partners, build positive relationships, and communicate complex concepts clearly to both technical and business audiences are necessary. Demonstrated commitment to continuous learning and development is also required.
Background in product engineering, hardware engineering, networking, semiconductors, or complex engineering organizations is desirable. Evidence of meaningful open-source contributions, including core commits, maintainership, widely adopted libraries, or public technical artifacts demonstrating system-level depth is also an advantage.