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AI Engineer with 1+ years in Agentic AI Systems & GenAI Platforms
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Backend Engineer with experience building scalable AI-native SaaS platforms, agentic AI systems, RAG pipelines, AI workflow orchestration platforms, and automation-first engineering solutions using Python and FastAPI. Skilled in LLM integration, vector databases, AI-assisted development workflows, workflow automation, SEO automation systems, and testing automation frameworks. Experienced with LangChain, LangGraph, n8n, Qdrant, PostgreSQL, Docker, Playwright, CI/CD, and modern AI engineering tooling. Focused on scalable backend architecture, AI operations enablement, and production-grade intelligent automation systems.
Lucknow Public College of Professional Studies
Bachelor of Computer Applications
August 1, 2021 – June 30, 2024
iValuePlus Services Pvt. Ltd.
Software Engineer (AI Backend & Agentic Systems)
December 1, 2024 – Present
Gurgaon, Haryana, India
BidSphere - AI-Native Bid Intelligence & Orchestration Platform
June 24, 2026 – Present
Developed backend systems for an AI-native bid orchestration and intelligent document processing platform. Built RAG-powered pipelines for tender analysis, contextual retrieval, and semantic document understanding. Implemented semantic capability matching using embeddings and vector database search. Designed explainable AI scoring systems for bid qualification and opportunity evaluation. Integrated AI agents for automated drafting assistance, bid analysis, and workflow orchestration. Contributed to scalable multi-tenant architecture supporting enterprise automation workflows.
AI-Driven Assessment & Evaluation Platform
June 24, 2026 – Present
Designed backend architecture for intelligent assessment lifecycle automation. Implemented AI-powered question generation workflows aligned with dynamic job descriptions. Built automated candidate evaluation and scoring pipelines using LLM-based analysis. Developed scalable APIs and orchestration workflows supporting multi-client adoption. Created AI-driven decision support systems for recruitment and candidate evaluation.
Cultural Fit Analysis
The candidate's projects demonstrate a strong focus on AI-native platforms and automation, aligning well with an innovative, fast-paced AI engineering environment. The breadth of technologies and integrations (e.g., Google APIs, WordPress MCP, Shopify CLI MCP) suggests adaptability and a willingness to work across different ecosystems. The experience with multi-tenant SaaS architecture indicates an understanding of enterprise-level solutions and scalability, which is a good fit for product-focused companies. However, the limited professional experience (starting Dec 2024) might indicate a need for mentorship in navigating complex organizational dynamics.
Soft Skills & Operational Fit
The candidate's resume highlights collaboration with QA teams and operational acceleration, suggesting a team-oriented approach and focus on practical, deployable solutions. The emphasis on 'automation-first engineering solutions' indicates a proactive mindset towards efficiency and operational excellence. The detailed project descriptions demonstrate an ability to articulate complex technical work clearly.