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Senior Python Backend Engineer

Rishi Prakash

I build production AI systems and high-performance backends in Python — real-time streaming, voice AI, and LLM integration that serve thousands of users at scale.

View my work Get in touch
7+
Years building
99.9%
Uptime shipped
<100ms
P95 latency

01 / About

From data science to AI engineering

I'm a Python backend engineer who came up through data science. Seven years ago I was building predictive models and analytics dashboards for Fortune 500 clients — today I architect the backend for an enterprise AI coaching platform: real-time streaming conversations, voice AI, and retrieval-augmented knowledge systems used by thousands of people.

That data background still shapes how I build. I care about measurable outcomes, clean data flow, and systems that hold up under real load — streaming under 100ms, designed for 99.9% uptime. Mostly, I like turning ambitious AI ideas into reliable software that ships.

Based in

Bengaluru

India · UTC+5:30 · open to remote

Currently

Real-time AI coaching @ Degreed

Streaming LLM conversations, voice agents, and RAG pipelines in production.

02 / Skills

Skills & tooling

Languages & Frameworks

  • Python 3.11+
  • FastAPI
  • Pydantic v2
  • asyncio
  • httpx
  • SQL
  • C# / .NET (integration)

AI / ML & LLM

  • Azure OpenAI
  • OpenAI Realtime API
  • RAG & embeddings
  • Function calling
  • Prompt engineering
  • Injection defense

Real-time & Streaming

  • Server-Sent Events
  • WebRTC
  • LiveKit
  • Async generators
  • Voice AI

Data & Storage

  • Redis Vector Store
  • Redis caching
  • PostgreSQL
  • MySQL
  • pandas
  • NumPy

DevOps & Observability

  • Docker
  • Kubernetes
  • Azure
  • DataDog APM
  • Prometheus
  • pytest / pytest-asyncio

Foundations

  • System design
  • Predictive modeling
  • NLP / topic modeling
  • A/B testing
  • Data visualization

03 / Experience

Experience

  1. 2024 — Present

    Senior Python Backend Engineer · Degreed

    Lead backend engineer for an enterprise AI coaching platform, building the Python/FastAPI services behind real-time coaching, voice, and assessment experiences used by thousands of learners.

    • Architected real-time AI conversations with FastAPI + Server-Sent Events, sustaining sub-100ms P95 streaming latency.
    • Built a voice-coaching capability on WebRTC and the OpenAI Realtime API with robust connection and quality monitoring.
    • Designed a retrieval-augmented knowledge base (vector search) so coaches answer from uploaded, domain-specific content.
    • Hardened the platform with multi-layer prompt-injection defense and a structured exception/error-code system.
    • Led a zero-downtime model migration with dual-model fallback, and cut Redis operations ~80% via unified session storage.
    • FastAPI
    • Azure OpenAI
    • Redis
    • LiveKit
    • DataDog

  2. Earlier

    Data Scientist / Senior Data Analyst · LatentView Analytics

    Delivered analytics and machine-learning solutions for Fortune 500 clients, turning messy data into decisions executives could act on.

    • Built predictive models and ML pipelines for client business problems.
    • Designed interactive Tableau and Qlik Sense dashboards for executive decision-making.
    • Ran NLP topic modeling (LDA) over large feedback corpora to surface themes.
    • Python
    • SQL
    • scikit-learn
    • Tableau
    • NLP

  3. 2018 — 2022

    Data Science & Analytics Roles · Multiple organizations

    Built the data foundation that still shapes how I engineer software today.

    • Developed ETL pipelines and BI reporting for stakeholders.
    • Performed statistical analysis and predictive modeling across domains.
    • Python
    • SQL
    • Statistics

  4. 2018 — 2019

    Business Analytics & Data Science · SSN School of Advanced Career Education (with IBM)

    Residential program: business statistics, BI & visualization, optimization, big data (Hadoop, Spark), and predictive analytics. GPA 8.4/10.

04 / Work

Selected projects

Real-time AI Coaching Engine

01
Problem
Coaching conversations need to feel instant, personal, and stateful — even under heavy concurrent load.
Approach
Streaming responses over Server-Sent Events with async generators, per-user context injection, and Redis-backed session persistence.
Outcome
Sub-100ms P95 streaming latency for thousands of concurrent sessions.
  • FastAPI
  • Azure OpenAI
  • SSE
  • Redis

Voice Coaching Platform

02
Problem
Make coaching feel like a real spoken conversation, not a chatbot with text-to-speech bolted on.
Approach
Live voice sessions on WebRTC and the OpenAI Realtime API, with structured event handling, transcription capture, and quality monitoring.
Outcome
Natural, low-latency voice coaching with automatic reconnection and call-quality safeguards.
  • LiveKit
  • OpenAI Realtime
  • WebRTC

RAG Knowledge Base

03
Problem
Coaches must answer from an organization's own documents — accurately and without leaking sensitive data.
Approach
A document pipeline with semantic chunking, vector embeddings, and approximate-nearest-neighbor retrieval, plus PII detection and masking.
Outcome
Sub-second, domain-specific retrieval that meets enterprise compliance needs.
  • Vector Search
  • Embeddings
  • Redis
  • PII masking

Prompt-Injection Defense

04
Problem
Any user-generated content is an attack surface for prompt injection against the model.
Approach
LLM-powered injection detection layered with auth, group, and entity validation, backed by a structured exception and error-code system.
Outcome
Hardened every user-content path with defense-in-depth and clear, secure error handling.
  • Security
  • Azure OpenAI
  • Pydantic

Details are kept high-level to respect employer confidentiality — happy to walk through architecture and trade-offs in conversation.

05 / Impact

By the numbers

0+

Years building software

0k+

Lines of production Python

0+

API endpoints shipped

0%

Uptime maintained

<0ms

P95 streaming latency

0

AI models integrated

06 / Contact

Let's build something

Have an ambitious idea?

I'm open to backend and AI/LLM engineering roles where I can ship reliable systems that put AI to real use. If that sounds like your team, I'd love to talk.

Email me Download résumé