• Design, develop, and maintain scalable ETL and ELT pipelines. • Build and optimize data architectures, databases, and data warehouses. • Integrate data from multiple sources, APIs, and third-party platforms. • Ensure data quality, consistency, reliability, and security. • Monitor and troubleshoot data pipelines and workflows. • Collaborate with analytics, engineering, and business teams to understand data requirements. • Implement data governance and best practices for data management. • Optimize data storage, processing performance, and query efficiency. • Support reporting, business intelligence, and analytics initiatives. • Document data models, workflows, and technical processes.

• Design and implement data integration and interoperability solutions across multiple systems and platforms • Design and maintain scalable data architectures and integration frameworks • Develop and maintain ETL/ELT pipelines for data ingestion, transformation, validation, and harmonisation • Design and implement interoperability middleware and API-based integration services • Develop and maintain data exchange mechanisms between heterogeneous systems • Design and implement canonical data models and metadata harmonisation processes • Support the implementation of surveillance, monitoring, and reporting data solutions • Develop and maintain cloud-based and hybrid data integration platforms • Ensure data quality, consistency, reliability, and performance across data ecosystems • Contribute to technical architecture decisions and interoperability standards implementation • Produce technical documentation, architecture artefacts, and implementation guidelines

Role Description Are you passionate about building scalable, high-performance data platforms? We are looking for a Senior Software Developer / Data Engineer to join our team and work remotely from Europe or Ukraine. In this role, you will contribute to a cutting-edge education technology initiative, designing and implementing a unified data integration platform that will serve as the foundation for an entire ecosystem. Why join us? You will work with modern technologies, collaborate with top engineers, and make an impact on a project that improves data governance, privacy, and compliance across the education sector. Job Description - Design and evolve the platform’s canonical data model - Architect and implement scalable data ingestion and synchronization frameworks - Build reliable, replayable, and highly scalable data processing pipelines - Design entity resolution and identity management capabilities - Define and implement data governance, lineage, and provenance standards - Drive architectural decisions related to scalability, resiliency, security, and operability - Collaborate with product and engineering teams to define platform capabilities and roadmap - Design APIs and delivery mechanisms for downstream consumers - Support customer migrations from legacy systems into the new platform - Mentor engineers and contribute to technical leadership across the team - Ensure platform reliability, performance, and operational excellence Qualifications - At least 5+ years of experience as a Software Developer or Data Engineer - Strong expertise in Java - Deep understanding of data platforms, integration platforms, or distributed systems - Hands-on experience with stream processing technologies (Apache Beam, Spark, Flink, Kafka Streams) - Experience designing and operating event-driven architectures - Strong data modeling and schema design skills - Experience with cloud-native architectures (GCP preferred) - Experience designing multi-tenant SaaS platforms - Strong understanding of data governance, lineage, data quality, and observability concepts - Proven ability to drive architectural decisions and technical initiatives - Strong communication and collaboration skills - Upper-Intermediate+ English level Requirements - Experience with Scala - Experience building Master Data Management (MDM) platforms - Experience with Customer Data Platforms (CDP) - Experience with identity resolution systems - Experience with Apache Beam/Dataflow in production environments - Experience with Cloud Spanner - Experience migrating large-scale legacy systems to cloud-native architectures - Experience leading platform engineering or data platform initiatives - Background in education technology or enterprise integration domains Benefits - Strong architectural thinking and technical leadership skills - Passion for building high-performance, scalable platforms - Comfortable mentoring peers and collaborating across teams - Proactive problem-solver with attention to detail - Committed to quality and operational excellence

Role Description We are seeking an experienced Senior AI Engineer to lead the design, development, and deployment of intelligent systems that drive business impact. You will own end-to-end AI solutions, set technical direction, and mentor other engineers, working across machine learning, LLMs, retrieval systems, agentic workflows, and the data layers that feed them. This role requires deep technical expertise and a track record of shipping production AI systems at scale. - AI Architecture: Architect AI systems end-to-end. Set technical direction. Review and mentor others’ designs. - LLM Strategy: Define how we use LLMs, routing, agentic orchestration, prompt patterns, fine-tune vs. prompt trade-offs, and model selection. - Production Ownership: Own deployment patterns across on-prem and cloud (Kubernetes, container infrastructure, secure integration). Drive operational excellence. - Data Architecture: Consult on the data layer, medallion design (bronze/silver/gold), RAG retrieval stores, schema evolution, drift detection, and query performance at scale. - Evaluation Framework: Define how we measure AI quality, use golden datasets, conduct judge-based eval, enable production observability (OpenTelemetry, Phoenix, or similar), and perform behavior testing. - Technical Leadership: Mentor AI Engineers, lead code and design reviews, set engineering standards for the AI team, and drive cross-team initiatives with Data Science and Data Engineering teams. - Security & PII: Set the bar for handling sensitive customer data, secure system design, authentication, PII safety, and compliance-aware patterns. - Collaboration: Partner with product managers, data scientists, engineers, and stakeholders to align AI solutions with business needs. Qualifications - Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field (or equivalent experience). - 5+ years of production software experience. - Strong proficiency with AI/ML frameworks (OpenAI SDK, Hugging Face transformers, agentic orchestration frameworks). - Strong Python AND strong SQL, both are first-class requirements. Comfortable with query optimization, indexing strategy, and data modeling. - Demonstrated experience designing and operating medallion architectures (bronze/silver/gold) at scale. - Experience handling data at scale, partitioning, batch pipeline design, query performance, and schema evolution. - Production LLM experience, prompt engineering, retrieval (RAG), agentic orchestration, fine-tuning trade-offs. - Experience with vector databases (pgvector, Pinecone, Weaviate, etc.) and production RAG patterns. - Experience with AI observability and evaluation frameworks, OpenTelemetry, Phoenix or equivalent, golden-set eval, and judge-based eval methodology. - Strong understanding of secure system design, authentication, API integrations, and PII-sensitive data handling. - Track record of mentoring engineers and shipping cross-team initiatives. - Strong problem-solving skills and ability to explain technical solutions to non-technical audiences. Preferred Skills - Hands-on experience with Model Context Protocol (MCP), building tools, OAuth flows, or MCP server integrations. - Experience leading data engineering or data platform initiatives end-to-end. - Experience with agentic AI frameworks (e.g., the OpenAI Agents SDK) in production. - Experience deploying production systems across both cloud (AWS, GCP, Azure) and on-prem environments. - Experience in fraud detection, financial services, or other PII-sensitive domains. - Knowledge of MLOps tools and CI/CD for AI. - Open-source contributions, conference talks, or technical writing in the AI/ML space. Benefits - Health & Wellness: Medical, dental, and vision coverage for you and your family. - Time Off: Paid time off, holidays, and personal days to maintain work-life balance. - Financial Growth: Competitive compensation, performance-based rewards, and local retirement or savings plans where applicable, along with financial education resources. - Career Development: Training programs, mentorship opportunities, and growth potential within the company. - Wellness Support: Mental health resources, fitness perks, and wellness programs. - Extras & Perks: Commuter benefits, employee discounts, and company-sponsored events. Additional Details - Potential Salary Range: $140-180k. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. - This role is eligible for remote US-based (work-from-home) locations. Chicago-based candidates would work in a hybrid capacity from the Accertify HQ located in Itasca, IL. - Visa Sponsorship: employment eligibility to work for Accertify in the U.S. is required, as Accertify will not pursue Visa sponsorship for this position.