Soumya Ranjan Das
Generative 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
Generative AI Engineer with 2+ years in LLMs, RAG & Agentic AI
Gen AI Engineer with 2 years of production experience building LLM-powered systems, RAG pipelines, and agentic AI solutions for enterprise clients. Delivered a natural language query engine on AWS Bedrock with a 10-12 second end-to-end response time, and a large-scale document intelligence pipeline that reduced processing latency by 70-75% (10-15 min to 3-4 min) at 300-400 documents daily for a US-based enterprise healthcare client. Strong client-facing delivery experience - translating ambiguous business requirements into production AI systems within a cross-functional, globally distributed team. Hands-on with LangGraph, FastMCP, RAG architectures (vector and knowledge-graph retrieval), and prompt engineering. AWS Certified Cloud Practitioner. Open-source agentic RAG system on GitHub.
Gandhi Institute For Technology
Bachelor of Technology · Computer Science & Engineering
August 1, 2020 – June 30, 2024
Hyscaler
Software Development Engineer I (AI/ML Integration)
April 1, 2024 – Present
India
Agentic RAG System
January 1, 2024 – June 1, 2026
Independently designed and built a production-grade agentic RAG system: LangGraph ReAct agent dynamically routing between Qdrant vector search and Neo4j knowledge-graph traversal - enabling multi-hop reasoning beyond standard single-index RAG. Full data pipeline: LlamaParse PDF extraction, HuggingFace embedding generation, LLM-driven knowledge graph construction - containerised with Docker Compose, async ingestion via Celery and Redis.
View ProjectAWS Certified Cloud Practitioner
Amazon Web Services
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's experience with diverse projects (healthcare, multi-tenant platforms) and technologies (Python, TypeScript, various LLMs, vector/graph databases) indicates adaptability and a broad technical interest. Their involvement in an open-source project (Agentic RAG System) suggests a collaborative mindset and a willingness to contribute to the community. The role at Hyscaler involves working in a cross-functional, globally distributed team, which aligns well with modern agile development environments. The breadth of skills and project diversity suggest a good cultural fit for a dynamic and innovative team.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through architectural redesigns that significantly improved system performance. Their experience in client-facing delivery and cross-functional collaboration indicates good communication and teamwork abilities. The independent development of an Agentic RAG system showcases initiative and self-sufficiency. The English test score of 59 suggests there might be some room for improvement in communication clarity, which is crucial for senior roles.