ScreenedIdentity Verified
No cost, no commitment - we'll make a personal intro
SP

Sai Prakash Sasubilli

Mid-level Full-Stack Software Engineer specializing in cloud-native web apps and AI agents

Peak Play AI SportsRivier UniversityNH, USA4 Years ExperienceMid LevelWorks Remote

Connect with Sai

Sai already has a relationship with Reval, so a warm intro from us gets a much better response than cold outreach.

Typically responds within 24 hours

Recommended

Already have an account?

About

Full-stack system analyst/programmer at PeakPlay Sports (startup) who built an AI "coach" product end-to-end in ~2 months, using a LangGraph-orchestrated multi-agent architecture with a FastAPI backend. Shipped production RAG grounded in athlete history (OpenAI embeddings + vector store) with guardrails and a structured eval loop (golden set + LLM-judge + human review) to improve engagement and reduce hallucinations.

Hire with Reval

Find your next great hire

Our AI agents source, screen, and vet candidates for your open roles. Get qualified candidates within 48 hours.

$250one-time kickoff
10%on successful hire
Post a Role90-day money-back guarantee

Key Strengths

  • Owned end-to-end build from architecture through deployment in a startup environment
  • Designed multi-agent LLM coaching system with parallel orchestration and conditional execution
  • Balanced latency vs response cohesion; improved synthesis via head-coach prompt/architecture changes
  • Improved user engagement by restructuring outputs into prioritized action items and table-based plans
  • Built production retrieval layer grounding outputs in athlete history using embeddings + vector search
  • Implemented LLM guardrails (relevance thresholding, source-attribution prompting) to reduce hallucinations
  • Created evaluation loop with curated golden set (40–50 cases), automated scoring, and weekly human review
  • Used eval findings to prevent regressions (ensured synthesis includes points from each coach, incl. biomechanics)
  • Built normalization and reliability layer for messy real-world inputs with graceful failure and retries
  • Implemented observability to trace raw vs normalized inputs, node execution, and report success/failure

Like what you see? We'll introduce you to Sai directly.

Experience

Software Engineer (Remote)Peak Play AI Sports · Jan 2025 – Present
Graduate Teaching AssistantRivier University · May 2024 – May 2025part-time
Software EngineerMagic Software · Jan 2021 – Jul 2023

Education

Rivier Universitymaster, Computer Information Systems
Bapatla Engineering Collegebachelor, Electronics and Communication Engineering

Languages

English

Certifications

Full-Stack Web Development with React (HKUST)5-Day AI Agents Intensive (Google & Kaggle)

Similar Candidates

Aditya Gupta - Senior Full-Stack Software Engineer specializing in cloud-native distributed systems and AI in San Francisco, CA

Senior Full-Stack Software Engineer specializing in cloud-native distributed systems and AI

San Francisco, CA13y exp
GoogleStanford University
View profile
JZ

Senior AI/ML Engineer specializing in applied AI and scalable backend systems

Palo Alto, CA14y exp
WaymoHarvard University
View profile
Fan Wang - Staff-level Software Engineer specializing in LLM inference infrastructure and scalable model serving in San Pablo, California

Staff-level Software Engineer specializing in LLM inference infrastructure and scalable model serving

San Pablo, California11y exp
OpenAINorthwestern University
View profile
CZ

Senior Full-Stack Engineer specializing in AI/ML platforms and cloud-native systems

Redwood City, CA12y exp
Fireworks AIUC Berkeley
View profile
CW

Senior AI/ML Engineer specializing in NLP, LLMs, and retrieval systems

Austin, TX11y exp
OptiverCarnegie Mellon University
View profile
IH

Ilija Hadzic

Screened ReferencesStrong rec.

Principal Robotics & Autonomy Research Engineer specializing in localization and multi-robot navigation

Murray Hill, NJ31y exp
Nokia Bell LabsUniversity of Pennsylvania

Highly experienced robotics software engineer building ROS/ROS2 systems for fleets of autonomous mobile robots (Clearpath Jackal/Husky and custom platforms), spanning localization, navigation, and multi-robot coordination. Has published work at ICRA (including RL-based local planning and heterogeneous robot coordination via a ROS-to-ZMQ bridge) and maintains open-source ROS modules, with strong simulation, debugging, and CI/CD practices.

View profile

Interested in Sai?

We'll personally introduce you - no strings attached.

For Hiring Teams

Build your dream team with Reval

Our AI agents source, screen, and vet candidates for your open roles. Get qualified, high-intent candidates on your desk within 48 hours.

$250one-time kickoff
10%on successful hire
48hrsto first candidates
Post a Role90-day money-back guarantee. A fraction of traditional agency fees.

Discover more candidates like Sai

Search across thousands of pre-screened, high-quality, high-intent candidates on Reval.

Search Talent

Connect with Sai

Sai already has a relationship with Reval, so a warm intro from us gets a much better response than cold outreach.

Typically responds within 24 hours

Recommended

Already have an account?

Hire with Reval

Find your next great hire

Our AI agents source, screen, and vet candidates for your open roles. Get qualified candidates within 48 hours.

$250one-time kickoff
10%on successful hire
Post a Role90-day money-back guarantee
Sai Prakash SasubilliMid-level Full-Stack Software Engineer specializing in cloud-native web apps and AI agents