Job Description

: Backend Engineer
Position Title: Backend Engineer (Fast Api/Go)
Location Onsite
Level Midlevel/Senior
Team: Zenteiq Platform Engineering
The Role
We're looking for a Backend Engineer to build and scale the core platform APIs, data layer, and microservices that power our platform engineering stack. This role is focused on production-grade backend systems, distributed infrastructure, and scalable deployment patterns.
You'll own:

• API development (FastAPI and/or Go microservices)

• Data layer design (PostgreSQL, Redis, NoSQL)

• Orchestration & scheduling (Airflow, Kubernetes)

• Event-driven workflows (Kafka / Pub/Sub)

• Cloud-ready deployments (Docker, Kubernetes, CI/CD)

• Production reliability (monitoring, logging, graceful degradation)

Key Responsibilities
? Core Development

• Build REST APIs for model registry, evaluation execution, and promotion workflows

• Design database schemas (PostgreSQL) with proper indexing, constraints, and migrations

• Implement async patterns for long-running tasks (Celery + Redis, Airflow)

• Build and maintain streaming / event-driven components using Kafka and/or Google Pub/Sub

• Write well-tested, maintainable, type-safe code (Python type hints + pydantic; Go strict typing)

? System Design

• Collaborate on architecture decisions (monolith vs microservices, sync vs async)

• Design for horizontal scalability (stateless services, connection pooling)

• Implement caching strategies (Redis) and query optimization

• Use NoSQL systems where appropriate for high-throughput or flexible-schema workloads

• Plan for reliability: backups, replication, failover, and service resiliency

? Integration & Ecosystem

• Build integrations for model serving and platform workflows (e.g., vLLM export hooks, storage integration)

• Integrate with tools and storage systems (GCS/S3, internal services)

• Build event-driven hooks for feedback loops and system workflows

? Operational Excellence

• Implement comprehensive logging, metrics, and tracing (e.g., Prometheus, Loki, Jaeger / OpenTelemetry)

• Ensure services are deployable and operable in containerized environments (Docker, Kubernetes)

• Document APIs (OpenAPI specs) and architecture decisions (ADRs)

• Participate in operational support and incident response when needed

Requirements
Required Skills
Backend Engineering

• 2+ years of production experience in Python and/or Go

• Strong experience building and maintaining REST APIs (FastAPI / Go frameworks)

• Strong understanding of async and concurrency patterns:

Python async/await, background tasks, Celery
Go routines, channels, context management

• Experience with PostgreSQL: schema design, indexing, migrations, query optimization

• Experience with Redis for caching, rate limiting, sessions, or task queues

• Familiarity with NoSQL systems (e.g., Firestore, MongoDB, DynamoDB equivalents), including when to use them

Event Driven and Distributes Systems

• Experience using messaging/streaming systems such as:

Kafka
Google Pub/Sub

• Understanding of distributed systems fundamentals:

eventual consistency, retries, idempotency, backpressure, load balancing

• Strong API design discipline:

OpenAPI/Swagger, API versioning, error handling, authentication patterns
Devops + Deployment

• Experience with containerized deployments:

Docker
Kubernetes (GKE or equivalent)

• Familiarity with CI/CD workflows and operational best practices (rollouts, rollbacks, configs, secrets)

• Basic familiarity with Google Cloud Platform (GCP) such as:

Cloud SQL, Cloud Storage, GKE, Pub/Sub
deploying + monitoring services in cloud environments
Quality and Collaboration

• Strong testing discipline: unit tests, integration tests

• Clear communication and documentation habits

• Comfortable with code reviews and iterative delivery

Nice To Have

• Experience with orchestration frameworks (Airflow or similar)

• Experience with observability stacks (Prometheus, Grafana, Loki)

• Familiarity with distributed tracing (Jaeger, OpenTelemetry)

• GraphQL experience (potential future direction)

• Experience working in compliance-conscious environments (SOC2, HIPAA, GDPR)

What we are looking for
1. Technical ownership: can design, build, and ship services end-to-end
2. Systems thinking: understands tradeoffs in architecture and reliability
3. Production mindset: writes operable code with strong debugging patterns
4. Pragmatism: chooses simple, robust solutions
5. Collaboration: works well with platform, ML engineers, and DevOps teams
Benefits
Working Environment & Culture

• Collaborative: Close partnership between ML, Backend, and DevOps teams; frequent pair programming and code reviews

• Innovation-Focused: Encouraged to research and experiment with cutting-edge agentic AI techniques

• Impact-Driven: Your work directly impacts millions of user

• Autonomous: Ownership of agent platform components with autonomy in technical decision-making

• Learning Culture: Access to conferences, courses, and mentorship to stay current with rapidly evolving agentic AI landscape

Learning & Growth

• Master MCP specification and contribute to community improvements

• Become the go-to expert for agentic AI systems within the organization

• Mentor junior engineers on agent architecture and best practices

Skills Required