Staff Engineer - Backend Platform

Role : SSDE / Staff Engineer Backend Platform :

Who are We :

Prismforce is a Vertical SaaS company transforming the Talent Supply Chain for global Technology, Engineering, and IT Services organizations.

Our AI-powered platform enables enterprises to improve operational agility, accelerate decisions, and increase profitability through intelligent workforce and talent infrastructure.

We are building large-scale, AI-native SaaS systems that operate across geographies, languages, tenants, and enterprise-scale workloads.

Job Title : Staff Engineer Backend Platform

Experience : 8 to 14 Years

Location : Bangalore / Pune

Employment Type :

• Full-time
  
  

Stack :

• Node.js
• TypeScript
• Distributed Systems
• Multi-Tenant SaaS
  
  

About The Role :

We are looking for a highly experienced Staff Engineer to lead the architecture and engineering of high-throughput, high-availability, multi-tenant SaaS platforms operating at global scale.

This role is for engineers who have designed and owned mission-critical backend systems handling large-scale concurrency, geo-distributed traffic, multilingual workloads, and enterprise-grade reliability requirements.

You will drive architecture decisions, platform scalability, database strategy, observability standards, and performance optimization across distributed systems.

You are expected to independently own applications end-to-end from architecture and design reviews to production reliability and engineering excellence.

This is a deeply technical leadership role.

We are looking for hands-on engineers who can solve hard systems problems, guide architectural direction, and elevate engineering quality across teams.

What Were Looking For Priority Order :

• Must Have Distributed Systems & Platform Architecture : Proven ownership of scalable, highly available SaaS systems
• Must Have CS Fundamentals & Runtime Internals : Strong expertise in concurrency, memory, CPU profiling, runtime behavior
• Must Have Database Design & Performance : Advanced schema design, indexing, partitioning, query optimization
• Must Have Multi-Tenant SaaS Architecture : Tenant isolation, scalability, geo-distribution, multilingual systems
• Strong Working Knowledge Reliability & Observability : Production monitoring, tracing, incident handling, SLO-driven systems
• Good to Have AI/LLM Infrastructure : Exposure to AI-native backend systems or agentic architectures
  
  

What Youll Do :

• Architect and own high-throughput, high-availability backend platforms serving enterprise SaaS workloads.
• Design globally scalable multi-tenant and multi-region systems with strong reliability guarantees.
• Drive application ownership end-to-end architecture, implementation, deployment, scalability, monitoring, and production operations.
• Build resilient distributed systems with asynchronous event-driven architectures.
• Lead platform-level decisions around scalability, caching, throughput optimization, resiliency, and fault tolerance.
• Diagnose and resolve CPU bottlenecks, memory leaks, event loop blocking, connection exhaustion, and distributed system performance issues.
• Define database architecture standards including indexing strategies, partitioning, sharding, replication, schema evolution, and query optimization.
• Drive engineering excellence across observability, testing, logging, tracing, CI/CD, and operational readiness.
• Lead high-level system design discussions and architectural reviews across teams.
• Mentor engineers on system thinking, debugging, scalability, and production-grade engineering practices.
• Collaborate with product and platform teams to design scalable multilingual and geo-distributed SaaS applications.
• Influence long-term platform strategy and technical direction.
  
  

Core Technical Expectations :

Distributed Systems & Scalable SaaS Architecture Bar-Raising :

This is the primary evaluation area for the role.

We are looking for engineers who have built and operated systems at scale not just contributed features.

Expected Expertise :

• High-throughput distributed systems design.
• High-availability and fault-tolerant architectures.
• Multi-region and geo-distributed deployments.
• Multi-tenant SaaS architecture patterns.
• Event-driven systems and asynchronous processing.
• Horizontal scaling strategies.
• Load balancing and traffic distribution.
• CAP theorem and consistency trade-offs.
• Resilience engineering and graceful degradation.
• Circuit breakers, retries, backpressure handling.
• Distributed caching and eventual consistency.
• API gateway and service mesh fundamentals.
• Queueing systems : Kafka, RabbitMQ, or equivalent.
  
  

Node.js Runtime & Systems Engineering Bar-Raising :

Deep runtime understanding is mandatory.

Expected Expertise :

• Node.js internals : event loop, libuv, V8 heap architecture.
• Worker threads, clustering, async execution models.
• Event loop blocking diagnosis.
• CPU and memory profiling in production systems.
• Heap snapshots, garbage collection analysis.
• Resource leak debugging.
• Process lifecycle and OS-level system behavior.
• Socket management and connection pooling.
• Performance optimization for long-running services.
• TypeScript at scale with strong type-system understanding.
  
  

Database Design & Performance Engineering Bar-Raising :

• We expect strong database architects not ORM-only developers.
  
  

Expected Expertise :

• Advanced relational database design.
• Query planning and execution analysis.
• Indexing strategies :
• B-tree.
• Composite indexes.
• Partial indexes.
• Covering indexes.
• Database partitioning and sharding.
• Multi-tenant data isolation models.
• Read/write scaling strategies.
• Replication and failover models.
• Schema migrations and zero-downtime deployments.
• MongoDB schema optimization and aggregation pipelines.
• Redis caching patterns and cache invalidation strategies.
• Data consistency and transaction management.
• Performance tuning under large-scale workloads.
  
  

High-Level Design & Architecture :

• You should be comfortable driving architecture for large-scale enterprise platforms.
  
  

Expected Expertise :

• System decomposition and domain-driven design.
• Service boundaries and communication patterns.
• Scalability estimation and capacity planning.
• Trade-off analysis across architecture choices.
• Design documentation and RFC creation.
• Production readiness reviews.
• Reliability-first engineering mindset.
• Security and tenant isolation awareness.
• Designing multilingual SaaS platforms.
• Designing geo-aware and region-aware systems.
  
  

Observability & Production Excellence :

Expected Expertise :

• Distributed tracing and observability.
• Prometheus, Grafana, OpenTelemetry.
• Structured logging and correlation IDs.
• Incident debugging and root-cause analysis.
• Defining meaningful SLIs/SLOs.
• On-call ownership and operational maturity.
• CI/CD pipelines and deployment strategies.
• Docker and Kubernetes production deployments.
  
  

Nice To Have :

• AI/LLM platform integration experience.
• Experience with agentic workflows or orchestration systems.
• Vector databases and semantic retrieval systems.
• Real-time transcript or speech-processing systems.
• Infrastructure-as-code exposure.
• Open-source contributions or technical writing.
• Prior experience in enterprise SaaS or platform engineering organizations.
  
  

The Kind Of Engineer Were Looking For :

• You think in systems, trade-offs, and long-term scalability.
• You naturally take ownership beyond your immediate module.
• You can simplify complexity without oversimplifying the problem.
• You are comfortable operating in ambiguity and high-growth environments.
• You care deeply about performance, reliability, and maintainability.
• You elevate engineering standards across teams through both execution and mentorship.
• You balance pragmatism with architectural rigor.
• You build platforms that other engineers love to work on.
  
  

(ref:hirist.tech)