Full Stack and AI Engineer

Role Description

Software engineering is the application of engineering to the design, development, implementation, testing, and maintenance of software in a systematic method. The roles in this function will cover all primary development activity across all technology functions that ensure we deliver code with high quality for our applications, products, and services and to understand customer needs and to develop product roadmaps.

• Design, build, and maintain scalable backend services and APIs using Java and Python
• Architect and implement event-driven/microservices solutions using Kafka (topics, partitions, consumer groups, schemas, retries/DLQs)
• Model, optimize, and maintain relational and/or NoSQL databases (schema design, indexing, query tuning, migrations)
• Develop data processing pipelines (streaming and batch) with strong focus on reliability, observability, and performance
• Build and integrate AI/ML-powered features (model inference services, prompt orchestration, vector search, or ML pipelines) and collaborate with data science teams
• Ensure production readiness: CI/CD, automated testing, monitoring/alerting, and incident response/root-cause analysis
• Enforce engineering best practices: code reviews, secure coding, documentation, and mentoring junior engineers
• Collaborate cross-functionally with product, QA, platform/SRE, and stakeholders to deliver roadmap initiatives

Qualifications

• High School Diploma/GED (or higher)
• 8+ years of professional software engineering experience building backend systems in Java and/or Python
• 5+ years of experience leading a team of 5-10 engineers
• 3+ years of experience with databases (PostgreSQL/MySQL/Oracle and/or MongoDB/Cassandra), including performance tuning and transactional consistency
• 3+ years of experience in cloud platforms (AWS/Azure/GCP), containerization (Docker/Kubernetes), and CI/CD
• 2+ years of experience with Kafka in production (exactly-once/at-least-once semantics, schema evolution, monitoring, capacity planning)
• 2+ years of experience designing distributed systems (microservices, REST/gRPC, concurrency, caching, resiliency patterns)
• 1+ years of experience delivering AI-enabled solutions (LLM integration, ML inference deployment, feature engineering, vector databases such as Pinecone/Weaviate/pgvector, or MLOps tools)

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science (or equivalent practical experience)

Soft Skills

• Strong problem-solving, communication, and ability to lead technical design discussions

Benefits

• Comprehensive benefits package
• Incentive and recognition programs
• Equity stock purchase
• 401k contribution (all benefits are subject to eligibility requirements)