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saravana87/README.md

Hi, I’m Sara👋

AI Engineer + Full-stack Architect with 14+ years of experience designing and delivering production systems across healthcare, insurance, and enterprise workflows.

I specialize in building LLM-native applications that combine strong software engineering fundamentals with practical GenAI architecture: retrieval, orchestration, observability, security, and cost-aware scaling.

Engineering Focus

  • LLM application architecture: RAG, agentic workflows, tool use, multi-step reasoning pipelines
  • Backend systems: Python (FastAPI, Flask), Node.js, TypeScript
  • Data & retrieval: PostgreSQL, pgvector, Redis caching, hybrid search, metadata-aware retrieval
  • Cloud & platform: AWS (Bedrock, Lambda, EC2, RDS, S3), Azure, GCP
  • DevOps & delivery: Docker, CI/CD, Nginx/Apache, Cloudflare, production monitoring patterns

Selected AI System Work

1) Clinical Intelligence Pipelines

Designed clinical summarization and extraction workflows over mixed-source content:

  • Inputs: text, PDF, image, and audio
  • Domain adaptation using biomedical model stacks (including BiomedBERT-based workflows)
  • Structured outputs for downstream review and decision support
  • Focus on reliability, reproducibility, and explainable output formatting

2) Insurance Appeal Automation

Built end-to-end automation for medical/insurance appeal generation:

  • Orchestrated AWS Bedrock + OpenAI model flows
  • Retrieval-grounded generation from policy/context documents
  • Deterministic prompt templates + post-processing guards
  • Reduced manual drafting effort and improved turnaround consistency

3) LLM Search & Assistant Platforms

Implemented chatbot/search platforms using:

  • LlamaIndex, LangChain, retriever composition, and reranking strategies
  • pgvector + PostgreSQL for semantic retrieval
  • Redis for caching frequent query paths and lowering latency/cost
  • Streamlit and web-based interfaces for rapid stakeholder validation

4) ClinicalTrials Conversational Layer

Engineered a conversational interface over clinical trial data:

  • Retrieval pipelines tuned for medical query intent
  • SQL-backed filtering + semantic matching
  • Caching and query optimization for responsive UX under repeated lookups

Private/Confidential Project Portfolio (NDA-safe Summary)

I’ve also led and shipped multiple private production initiatives, including:

  • Secure internal copilots for domain teams with role-aware retrieval
  • Confidential document intelligence systems for policy/clinical records
  • Multi-tenant AI workflow backends with audit-friendly processing
  • API/webhook automation across communication and operational systems
  • Architecture modernization from legacy service layers to cloud-native components

I can provide deeper architecture walkthroughs, redacted diagrams, and implementation details during interviews.

Technical Stack

Languages & Frameworks

  • Python, TypeScript, JavaScript
  • FastAPI, Flask, Node.js
  • React, Next.js

AI / NLP

  • OpenAI APIs, AWS Bedrock
  • LlamaIndex, LangChain
  • Embeddings, vector retrieval, prompt chaining, evaluation loops

Data

  • PostgreSQL, MySQL, Oracle, SQL Server
  • pgvector, Redis
  • ETL/normalization pipelines for unstructured and semi-structured documents

Cloud / Infra

  • AWS, Azure, GCP
  • Docker, CI/CD
  • Nginx, Apache, Cloudflare

Architecture Principles I Follow

  • Grounding first: retrieval before generation for factual tasks
  • Deterministic where possible: templates, validation, structured schemas
  • Latency/cost awareness: cache strategy, model routing, token discipline
  • Security by design: scoped access, data handling boundaries, least privilege
  • Observability: traceable pipeline steps, error buckets, feedback loops
  • Production readiness: graceful fallbacks, retry logic, and measurable SLAs

Certifications

  • AWS Cloud Practitioner
  • AWS Developer Associate
  • AWS Solutions Architect Associate

Open To

  • Senior/Lead AI Engineer roles
  • Founding Engineer opportunities (0→1 product + platform buildout)
  • High-ownership roles spanning architecture, implementation, and delivery

Contact

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