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Mahesh Kadambala
Client Capabilities & Offerings

Backend Engineering, SaaS Architecture & AI Integration

I provide senior engineering horsepower to solve complex architectural challenges, build resilient multi-tenant platforms, integrate practical AI workflows, and eliminate database bottlenecks.

Core Architecture01

SaaS Backend Engineering

High-concurrency APIs, multi-tenant data isolation, and robust backend systems built to scale without rewrites.

I design and build production-grade backend systems for B2B SaaS platforms. From schema-per-tenant isolation to high-throughput REST/GraphQL APIs and transactional data pipelines, I ensure your core platform is resilient, secure, and maintainable.

Problems Solved

  • Application performance slowing down as customer and tenant volume grows
  • Risk of cross-tenant data leaks and compliance exposure in B2B environments
  • Fragile business logic scattered across monolithic controllers with no clear domain boundaries
  • Complex authorization and multi-role permission requirements

Typical Deliverables

  • Multi-tenant backend architecture with fail-closed schema or row isolation
  • High-throughput, tenant-scoped REST/GraphQL APIs with sub-100ms response targets
  • Enterprise authentication & RBAC (JWT rotation, session security, SSO readiness)
  • Automated integration test suites with real databases using Testcontainers
  • Comprehensive API documentation, OpenAPI specifications, and architecture decision records (ADRs)

Ideal For:

Early-to-growth stage SaaS founders building their core platformCTOs needing senior engineering firepower for critical backend milestonesProduct teams launching enterprise-tier multi-tenant offerings
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Intelligent Workflows02

AI Integration for SaaS

Embed LLMs, AI agents, RAG pipelines, and intelligent workflows directly into your existing SaaS products.

Transform your product with practical AI capabilities that solve real user friction. I integrate LLM workflows, retrieval-augmented generation (RAG) over your proprietary data, knowledge graphs, and automated agentic pipelines without destabilizing your existing production architecture.

Problems Solved

  • Need to add AI features quickly without breaking existing database schemas and transactional flows
  • LLM outputs hallucinating or lacking context on customer-specific data and tenant permissions
  • High API costs, uncontrolled latency spikes, and rate-limiting from direct LLM provider calls
  • Uncertainty on how to securely ground AI responses within strict multi-tenant boundaries

Typical Deliverables

  • Tenant-isolated RAG pipelines with vector databases (pgvector, Elasticsearch, Qdrant)
  • Deterministic AI agent workflows with human-in-the-loop approval hooks
  • Structured output validation and automated fallback mechanisms
  • Asynchronous background processing for long-running AI operations with webhooks and status streaming
  • Cost-optimized prompt engineering, response caching, and model orchestration

Ideal For:

SaaS companies wanting to add high-value AI assistants and automated operationsFounders modernizing traditional workflow tools with intelligent automationTeams needing secure, tenant-safe document search and Q&A over enterprise datasets
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Distributed Systems03

System & API Integration

Reliable event-driven pipelines, third-party platform integrations, and asynchronous messaging that never drop data.

Connect disconnected platforms, internal microservices, and external enterprise systems. I build fault-tolerant event pipelines using Kafka, SQS, and the Transactional Outbox pattern so your data stays synchronized even during network partitions and provider outages.

Problems Solved

  • Dual-write bugs and silent event loss when databases and message brokers fail asynchronously
  • Unreliable third-party API webhooks causing duplicate billing or missed business events
  • Data silos between internal services requiring constant manual reconciliation
  • Slow, tightly coupled synchronous HTTP calls causing cascading system outages

Typical Deliverables

  • Transactional Outbox implementation with guaranteed at-least-once message delivery
  • Idempotent consumer handlers with dead-letter queue (DLQ) automated retry and alert policies
  • Custom bi-directional webhooks and third-party SaaS integrations (Stripe, HubSpot, ERPs)
  • High-throughput batch ingestion and streaming data pipelines
  • Distributed tracing, structured logging, and observability dashboards

Ideal For:

Platforms integrating with multiple enterprise APIs, payment gateways, or ERPsEngineering teams decomposing monoliths into event-driven microservicesBusinesses experiencing distributed data inconsistencies and phantom bugs
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Performance & Rescue04

Backend Modernization & Rescue

Diagnose slow queries, eliminate database bottlenecks, untangle legacy codebases, and stabilize fragile production systems.

If your production backend is struggling with slow response times, recurring downtime, or technical debt that grinds feature development to a halt, I step in to diagnose root causes, optimize database queries, refactor critical paths, and restore stability.

Problems Solved

  • Database queries choking under heavy traffic with high CPU and connection exhaustion
  • Endpoints with 2+ second p95 latency damaging customer retention and conversion
  • Fear of deploying updates because the legacy codebase is brittle and untested
  • Memory leaks, unindexed table scans, and unoptimized ORM queries (N+1 problems)

Typical Deliverables

  • In-depth architectural and database performance audit with actionable priority matrix
  • PostgreSQL query optimization, composite indexing, and connection pool right-sizing (cutting latencies up to 60%)
  • Zero-downtime database schema migrations and refactoring of high-risk endpoints
  • Automated test coverage on critical business paths to allow fearless deploys
  • Clear engineering roadmap and handover documentation for your internal team

Ideal For:

Founders dealing with sluggish applications losing customer trustCTOs taking over legacy codebases that need rapid stabilizationCompanies preparing their backend infrastructure for an upcoming traffic surge or enterprise pilot
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Have a Specific Backend or AI Problem?

Whether you need a full platform build, an AI integration audit, or database latency optimization, let's discuss the architecture.