Senior Software Engineer – Forecasting & Recommendations
Zeta Global (company site, opens in a new tab)8–12 yrsBengaluruOn-siteDirect career pageEst. 30–48 LPA
Posted on 15 Sept
Reach people at Zeta Global
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Zeta Global you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, build, and operate backend services that support forecasting, recommendations, and Performance Advisor workflows at scale.
- Own significant backend distributed systems and components from design through deployment, incident resolution, and continuous improvement.
- Collaborate with data science and product teams to integrate AI and machine-learning driven capabilities into production systems while ensuring reliability, observability, and operational excellence.
Minimum Requirements
- 8–12 years of professional experience building and operating scalable backend systems.
- Strong hands-on expertise with distributed systems design, event-driven systems, backend APIs, and cloud-native operations on AWS.
- Experience with Kafka, Elasticsearch, NoSQL databases (e.g., Aerospike), container-based microservices, and proficiency in backend languages such as Python, Java, Ruby, Go, or Scala.
- Bachelor's or master's degree in Computer Science, Mathematics, Engineering, or related field, or equivalent practical experience.
Ideal Candidate Profile
- Demonstrated ownership of production-grade, high-throughput, low-latency distributed services integrating forecasting, recommendation, or AI-driven workflows.
- Experience balancing technical and product trade-offs to deliver practical, reliable, and maintainable backend solutions in large, distributed teams.
- Strong system design and operational mindset with a record of mentoring engineers and driving improvements in reliability, scalability, and team velocity.