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Gourab Bank

Open to work1 years experience

Full-Stack AI Engineer

Mumbai, IndiaTarget Roles: Backend Engineer • Full-Stack Developer • Frontend Specialist

Full-Stack AI Engineer building production RAG systems, LLM applications, and distributed backends.

GitHub

Standing Rank

Rank Not Available

Developer Badges

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Skills & Technologies

23 skills
pythonjavatypescriptsqlbashfastapispring bootkafkareactnext.jspostgresqlredismongodbawsgcpdockerairflowlangchainlanggraphfaisspgvectorprompt engineeringllm evaluation

Work Experience

Full-Stack AI Engineer

Zenziee

Jan 2026 - Present Mumbai, India
  • Core engineer on a RAG platform indexing 150K+ freight regulations and carrier contracts; implemented hybrid retrieval (FAISS/pgvector dense search with BM25 re-ranking) serving queries at sub-200ms p99 latency.
  • Built the chunking, embedding-generation, and metadata-tagging stages of the document ingestion pipeline, with automated tests covering retrieval and incremental re-indexing on policy updates.
  • Developed prompt and agentic-workflow logic for an LLM dispute-resolution assistant that cut average resolution time from 48 hours to under 8 hours.
  • Diagnosed a 6-hour Kafka consumer offset lag on a pipeline handling 3M+ weekly shipment-tracking events; resolved it via partition rebalancing and consumer-group tuning.
  • Added Grafana dashboards tracking retrieval latency, chunk hit-rate, and LLM token spend.

Software Development Engineer

D&D Motor Systems

Jan 2025 - Dec 2025
  • Built a customer-facing service booking portal (React/TypeScript frontend, Java/Spring Boot backend) supporting real-time repair scheduling for 20+ daily technicians.
  • Implemented a LangGraph-based workflow that auto-routed incoming repair requests to technician queues, reducing manual processing time by roughly 35%.
  • Developed Python/FastAPI microservices for request routing and data writes with 80%+ test coverage, load-tested to sustain 500 RPS at p95 latency under 120ms.
  • Contributed to an Airflow ETL pipeline pulling telematics data from 4 vendor APIs into PostgreSQL, helping cut daily pipeline failure rate from 12% to under 1%.
  • Helped build a RAG-based internal knowledge assistant over 8 years of service manuals, reducing technician lookup time by about 40%.

Projects

Projects Not Populated

Personal applications, open-source work, and code repos will show here.

Leaderboard Standings

Leaderboard Position Pending

Global test scores, peer standing percentiles, and algorithm leaderboard ranks are updated dynamically.

Assessment Highlights

Assessments Not Completed

Coding evaluations, system assessment results, and conceptual score badges will appear here after taking a test.

AI Collaboration Score

AI Collaboration Score Pending

Developer coding behavior, assistant cooperation, and AI pair-programming indicators are evaluated during live coding sessions.

Role Compatibility Profile

Role Compatibility Analysis Pending

Custom matching reports, candidate role compatibility percentiles, and core engineer strength profiles are processed once conceptual code screenings are complete.

Achievements

Project Helix - LLM Benchmarking & Golden Solutions

Authored golden reference solutions for complex SWE-bench tasks used as ground truth in LLM code-generation benchmarks; built a patch-scoring rubric adopted as the team standard.

Project Escher - Visual Reasoning Evaluation for VLMs

Evaluated charts, diagrams, and real-world scenes to surface VLM failure modes; findings fed into model training data pipelines.

About Details

Professional Bio

Full-Stack AI Engineer with 1.5+ years of experience building production RAG systems, LLM applications, and distributed backends. Expert in Python, FastAPI, Java, Spring Boot, Kafka, and React. M.S. in Computer Science from Syracuse University.

M.S. in Computer Science

Syracuse University (2023 - 2025)

Bachelor of Engineering – Computer Engineering

VESIT, Mumbai University (2019 - Present)

Languages: English, Hindi
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