Bhupesh Pandey
Bhupesh Pandey

Bhupesh Pandey

Backend • Middle • Management: 3-5 years (6-15 people) • 43 years • Bengaluru, India • UTC+05:30 • Partially remote • Work permits: India • Citizenship: India • Available in 1 week • from $80k per year
Software Developer
11+ years exp
Management: 3-5 years (6-15 people)
Go
TypeScript
Node JS
Python
SQL
JavaScript
Active 17 days ago
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Overview
Technical skills
Timeline
Roles

Overview

Backend API engineer (Middle level) focused on small Go-based HTTP services and in-memory data structures with concurrent access control. The strongest proven skill is implementing server-side graph logic and a BFS shortest-path over a concurrency-safe in-memory store as implemented in internal/graph/graphstore.go. There is no evidence of production concerns such as persistent databases, migration history, authentication, observability, or distributed system design.
Phone

Technical skills

Languages
6
Go
TypeScript
Node JS
Python
SQL
JavaScript
AI/ML
3
Gemini
LangGraph
Vertex AI
DevOps
6
Kubernetes
GitLab
GitLab CI
CI/CD
Datadog
Prometheus
Other
12
Redis
PostgreSQL
Pydantic
FastAPI
External Secrets
LLM
SQLAlchemy
LangChain
DeepEval
Rest API
Apache Kafka
Model Context Protocol

Timeline

Staff Software Engineer • Lead
Applied Systems India • Full-Time
Sep 2024 to Present 2 Years 1 Month Bengaluru In office
Worked on AskEva, an AI assistant embedded in EZLynx for answering questions about applicants, policies, claims, and billing. Built and maintained an agent service with JWT auth, PostgreSQL-backed conversation state, LangGraph routing, safety filtering, and structured Pydantic responses with citation links and PII scrubbing. Developed an MCP sidecar for applicant/policy/claims/billing tools and integrated Vertex AI Search, while adding Datadog-based observability, GitLab CI evaluation gates, and Kubernetes deployments with Vault/External Secrets.
LangGraph
Gemini
Vertex AI
FastAPI
Pydantic
PostgreSQL
Datadog
Prometheus
Kubernetes
Redis
External Secrets
GitLab
GitLab CI
CI/CD
Back End Developer • Middle
IBM • Full-Time
May 2022 to May 2024 2 Years In office
Built and operated cloud-based REST APIs on IBM Cloud that brokered traffic between front-end and back-end systems for production workloads. Owned production support responsibilities including Sev1/Sev2 incident triage, cross-team root-cause analysis, and postmortems with corrective actions. Improved deployment, monitoring, and alerting practices to meet availability and latency SLOs and reduce repeat defects through quality gates.
Principal Software Engineer • Lead
F5 • Full-Time
Oct 2021 to May 2022 7 Months In office
Designed and operated services for F5’s crypto platform, including secure key creation, storage, and retrieval. Implemented operational standards with meaningful monitoring agents and severity-tiered escalation aligned to documented playbooks, and supported production on-call and RCA workflows. Contributed to incident-management reporting and follow-up defect tracking after production issues.
Redis
Senior Technical Lead • Lead
Infinite Computer Solutions • Full-Time
Nov 2020 to Oct 2021 11 Months In office
Managed program timelines, resourcing, and stakeholder communications across parallel engineering workstreams while maintaining agreed quality bars. Established standardized incident-response and deployment processes and drove tooling rollouts to improve operational execution. Mentored engineers through brown-bags, postmortem reviews, and structured guidance.
Project Lead • Lead
Persistent Systems • Full-Time
Aug 2020 to Nov 2020 3 Months In office
Led a senior engineering pod delivering cloud-native solutions and aligned delivery scope and design with client stakeholders. Coordinated operational readiness activities for releases to ensure smooth handover and support. Owned day-to-day planning and execution alignment for the pod’s technical deliverables.
Project Lead • Lead
L&T Technology Services • Full-Time
Oct 2015 to Feb 2020 4 Years 4 Months In office
Owned design, delivery, and 24x7 operational responsibility for high-throughput streaming and industrial IoT data platforms. Built backend components including a Go-based data exchange platform, Go/Node.js telemetry ingestion, Go-based Modbus REST connectors, and TypeScript middleware for rig activities. Drove incident response and root-cause analysis and partnered with US-based product teams onsite to improve operational tooling for oilfield workloads.
Go
Node JS
TypeScript
Senior Engineer • Senior
Continental Automotive Components Ltd • Full-Time
Apr 2012 to Dec 2013 1 Year 8 Months In office
Built diagnostic configuration capabilities for automotive systems using Core Java and Eclipse plugin frameworks. Created an EcuSpectrum plug-in on the ARTOP framework to enhance diagnostic tooling for automotive ECUs. Worked on safety-critical diagnostics tooling with emphasis on reliability and maintainability.
Senior Software Engineer • Senior
KPIT Cummins Infosystems Ltd • Full-Time
May 2008 to Apr 2012 3 Years 11 Months In office
Developed applications using Core Java and Eclipse-based frameworks (EMF, SWT, JFace) and maintained code quality for production usage. Resolved Jira-tracked defects using root-cause analysis and disciplined debugging processes. Mentored junior engineers on coding standards and professional growth practices.
Pune University
Non-Degree Program
Pune, Maharashtra
Middle Backend Developer Confidence: High API Engineer
Backend API engineer (Middle level) focused on small Go-based HTTP services and in-memory data structures with concurrent access control. The strongest proven skill is implementing server-side graph logic and a BFS shortest-path over a concurrency-safe in-memory store as implemented in internal/graph/graphstore.go. There is no evidence of production concerns such as persistent databases, migration history, authentication, observability, or distributed system design.
API Design
3/10
How well APIs are designed
Basic HTTP API design implemented with simple handlers and method checks but no versioning, pagination, idempotency, or consistent error contract; path parsing is manual and brittle.
Evidence
graph-server/internal/server/handlers.go: handlePostGraph, handleGetShortestPath, handleDeleteGraph - manual path parsing and JSON responses
graph-server/internal/server/server_test.go: Test_RegisterHandlers - verifies handler registration for endpoints
Data Layer & Database
3/10
Working with databases
In-memory data layer with RWMutex protecting a map and unit tests; no database integration, schema evolution, transactions or tuned queries are present.
Evidence
graph-server/internal/graph/graphstore.go: GraphStore with sync.RWMutex and map[string]model.Graph
graph-server/internal/graph/graphstore_test.go: tests for Add/Get/Delete and shortest-path behavior
Scalability & Performance
3/10
Handling load and speed
Shows performance awareness via benchmark tests and uses concurrent-safe locks, but lacks caching strategies, queueing, rate limiting, or load-management design.
Evidence
graph-server/internal/graph/graphstore_bench_test.go: BenchmarkGraphStore_AddGraph and BenchmarkGraphStore_GetGraph
graph-server/internal/server/server_test.go: BenchmarkServe and endpoint benchmarks
System Architecture
3/10
Overall system structure
Reasonable package separation into internal/server and internal/graph indicating modular design, but overall a single-process monolith without config management, service contracts, or graceful degradation strategies.
Evidence
graph-server/cmd/main.go: application entry (module separation)
graph-server/internal/graph/graphstore.go: encapsulated graph storage logic
Security & Auth
2/10
Protecting data and access
Minimal security posture - no authentication/authorization, limited input validation beyond JSON unmarshal, and error messages can leak internal error objects.
Evidence
graph-server/internal/server/handlers.go: error responses encode raw errors and path parsing is unchecked
graph-server/internal/graph/graphstore.go: AddGraph uses json.Unmarshal without schema validation beyond the model type
Reliability & Observability
2/10
Stability and monitoring
Has unit tests and benchmarks which help reliability, but lacks structured logging, metrics, timeouts, graceful shutdown, retries with backoff or circuit-breaking patterns.
Evidence
graph-server/internal/server/server_test.go: unit tests and benchmark coverage for handlers
graph-server/internal/graph/graphstore_bench_test.go: benchmark coverage for store operations
Expertise
Go Development• Middle
Microservices & API Architecture• Middle
Technologies
Go• since 2015 • Senior
Node JS• since 2015 • Middle
Rest API
FastAPI• since 2024
Apache Kafka
Recommendations
  • Develop small internal APIs and prototypes that need fast iteration and in-memory processing, where the current in-memory store is acceptable.
  • Extend the existing graph service to add persistent storage, schema migration, and durability (Postgres or similar) while preserving current tests and benchmarks.
  • Harden HTTP handlers by adding structured logging, request timeouts, input validation, and authentication/authorization.
  • Implement observability (metrics, traces, logs) and graceful shutdown to prepare the service for production deployment.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories:
graph-server cronjobcli
Middle DevOps Engineer Confidence: Medium Generalist
A middle-level Go engineer focusing on small, concurrent backend services with a clear emphasis on test coverage and micro-scale reliability. The strongest proven skill is implementing a concurrency-safe in-memory graph store and BFS shortest-path logic, demonstrated by internal/graph/graphstore.go with accompanying tests in internal/graph/graphstore_test.go and benchmarks in internal/graph/graphstore_bench_test.go. There is no public evidence of CI/CD pipelines, production container orchestration, observability, or cloud infrastructure automation in the credited files.
CI/CD Pipelines
Automated build and deploy
Not evidenced in public code
Infrastructure as Code
Managing servers with code
Not evidenced in public code
Containerization & Orchestration
Working with containers
Not evidenced in public code
Observability & Monitoring
Watching system health
Not evidenced in public code
Reliability & Incident Response
3/10
Keeping systems up
Application reliability is evidenced through unit tests and benchmarks plus concurrency-safe in-memory store design; there are no runbooks, incident playbooks, or rollout/rollback strategies.
Evidence
graph-server/internal/graph/graphstore_test.go
graph-server/internal/graph/graphstore_bench_test.go
graph-server/internal/graph/graphstore.go
Cloud & Cost Optimization
Smart use of the cloud
Not evidenced in public code
Recommendations
  • Assign to build lightweight Go microservices or internal platform components that require in-memory data structures and concurrency safety.
  • Have the developer expand production readiness by adding CI/CD workflows, container image optimization, and deployment manifests with rollback criteria.
  • Task the developer with improving observability by adding application metrics, structured logs, and basic SLOs and alerting tied to tests and benchmarks.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories:
graph-server cronjobcli