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 :

1. B-tree.

2. Composite indexes.

3. Partial indexes.

4. 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.