BackEnd Engineer

Job Description: Backend Engineer

Position Title: Backend Engineer (Fast Api/Go)

Location Onsite

Level Midlevel/Senior

Team: Zenteiq Platform Engineering

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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

Ø   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)

Ø   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

Ø   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

Ø   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