Rohit Ravindra Bhesurwar
AI EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
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 Engineer with 2+ years in Python, GenAI solutions, and scalable backend development.
Python Developer with 2+ years of experience building scalable backend applications and Al-driven GenAl solutions using FastAPI, RAG (Retrieval-Augmented Generation), and LLM-powered services. Strong proficiency in Python development with hands-on experience across SQL and MongoDB databases, REST APIs, and backend architecture. Proven expertise in Azure OpenAI, AWS, vector databases, prompt engineering, and microservices architecture. Skilled at building chatbots, copilots, document intelligence, and knowledge retrieval solutions that deliver measurable business impact. Strong problem-solving and communication skills with a results-driven ownership mindset in agile, cross-functional teams.
Savitribai Phule Pune University
B.E. · Computer Science
August 1, 2020 – June 30, 2024
Randstad (Client: NVIDIA)
Associate AI/ML Developer
August 1, 2024 – Present
Pune, Maharashtra, India
SpikeROAS
Software Engineer - GenAI & Backend
February 1, 2024 – July 1, 2024
India
AI Risk Intelligence Platform (Credit Risk Engine)
June 1, 2026 – Present
Production GenAI financial risk engine built with FastAPI microservices, combining RAG-based policy retrieval (pgvector + Azure AI Search) and Azure OpenAI GPT-4 natural-language explainability. Classified applicants high/medium/low risk with streaming LLM responses, OTEL observability, and OAuth 2.0 authentication; applied prompt orchestration, chunking strategies, caching, and batching for low-latency, cost-efficient LLM inference deployed on AWS.
View ProjectRAG-Based Memory Search Engine
June 1, 2026 – Present
Built a production-grade GenAI-powered search engine combining RAG-based retrieval, FAISS vector memory, and Google Gemini 2.5 Flash to deliver AI-synthesized, citation-backed answers via FastAPI microservices. Designed a hybrid ranking algorithm (semantic similarity + keyword overlap + provider weight) and an agentic multi-step reasoning loop with self-evaluating refined sub-queries for complex questions. Implemented Redis caching, FAISS persistent vector memory for contextual recall, streaming LLM responses, and Docker-based deployment - delivering low-latency, cost-efficient GenAI inference at scale.
View ProjectFull Stack Development in Python
SevenMentor Institute
June 1, 2026 – Present
AWS Cloud
Infosys Foundation
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including a financial risk engine and a memory search engine, demonstrates a broad application of GenAI skills. Their experience at Randstad (client: NVIDIA) and SpikeROAS, coupled with personal projects, shows adaptability and a proactive approach to learning and applying new technologies. The skills listed align well with an AI Engineer role, indicating a strong cultural fit for a technically demanding environment. However, the experience level (2 years) might be on the lower end for a senior AI Engineer role, which could impact cultural fit in terms of mentorship and leadership expectations.
Soft Skills & Operational Fit
The candidate's resume highlights collaboration with product managers, data scientists, and platform engineers in agile sprints, indicating good team collaboration and operational fit. The description of optimizing inference pipelines and ensuring production readiness suggests a results-driven and ownership mindset. However, without specific psychometric test results, a deeper assessment of stress handling and work attitude is not possible.