Sathwik Bidayath
Open to work3 years experienceAI Engineer
AI Engineer specializing in Multi-Agent Systems, LLMOps, and Workflow Automation.
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Skills & Technologies
27 skillsWork Experience
AI Engineer
Yash Technologies
- Led design and implementation of an enterprise multi-agent AI platform within a 3-person engineering team, focused on intelligent task orchestration and workflow automation.
- Architected and deployed production AI agents using LangGraph and Google ADK in a Hub-and-Spoke architecture with tool calling, centralized request routing, and shared state management.
- Built stateful workflow orchestration with pause/resume capabilities and persistent execution context across multi-step, long-running processes.
- Developed secure tool execution pipelines by integrating external MCP services for real-time flight search, with subprocess isolation, retry logic, and input validation for reliable tool execution.
- Integrated hybrid retrieval and contextual document search to provide relevant knowledge during multi-agent workflow execution.
- Implemented execution guardrails including reasoning-depth controls, action tracking, and duplicate task prevention to improve workflow stability.
- Containerized AI services and standardized deployment workflows, simplifying environment portability and operational maintenance.
- Collaborated with product and engineering stakeholders to convert business requirements into production-ready AI automation workflows.
- Implemented AI guardrails including authentication, authorization, PII protection, and secure tool access.
Infra Managed Analyst
Accenture
- Built and deployed a Python-based SOP chatbot enabling operations teams to query standard operating procedures through a web interface, eliminating the need to manually search across 80+ documentation pages for routine operational tasks.
- Automated vendor ordering workflows using Selenium and Google Sheets, deployed on AWS with scheduled execution, removing a recurring 45-minute daily manual process and ensuring uninterrupted task execution across shifts.
- Designed and implemented Power BI dashboards for monitoring ticket aging across multiple SLA buckets (15–30, 31–60, 61–90, and 90+ days), providing daily visibility into escalation risk and workload distribution across a 12-member operations team.
- Built MTTR, KPI, and SLA reporting workflows using ServiceNow data, enabling engineering managers to generate client-facing operational reports without manual data aggregation and establishing the dashboard as the team’s primary reporting tool.
Infra Managed Service Associate
Accenture
- Owned end-to-end Critical Incident Management (CIM) across a portfolio of enterprise clients, coordinating cross-functional stakeholders, documenting root cause analyses (RCA), and consistently meeting all six tracked SLA/KPI targets through ServiceNow workflows.
- Built and maintained ServiceNow dashboards for incident lifecycle monitoring, replacing ad hoc spreadsheet reporting with structured SLA and KPI reporting for weekly client and stakeholder reviews.
- Managed CMDB configuration lifecycle for virtual machines, physical servers, and network assets, maintaining data integrity through P*Q reconciliation and generating audit-ready reports for quarterly compliance reviews.
Projects
ContinuaEval
View Project- Built a continuous evaluation framework for production LLM applications that combines deterministic metrics, LLM-as-a-Judge scoring, groundedness, behavioral drift detection, and regression testing to monitor model quality over time.
- Implemented configurable evaluation pipelines with regression gates and rollback safeguards to prevent degraded model behavior from reaching production workflows.
- Designed a modular evaluation framework supporting custom metrics, judge providers, and benchmark datasets for repeatable experiments.
DocMind
View Project- Developed a production-oriented Retrieval-Augmented Generation (RAG) system that ingests PDF documents, performs semantic retrieval using FAISS, and generates citation-backed answers with Gemini.
- Developed document ingestion, semantic chunking, embedding, and indexing pipelines to support efficient semantic search across large PDF document collections.
- Integrated automated RAG evaluation and failure analysis to measure retrieval and generation quality, making it easier to diagnose hallucinations and retrieval issues.
Model Serve
View Project- Developed a production-style AI model serving platform with versioned model deployment, REST inference APIs, and a registry for managing model releases.
- Implemented LLMOps foundations including request routing, health checks, audit logging, Prometheus-based observability, latency monitoring, throughput tracking, and service reliability metrics.
- Implemented canary deployment and rollback infrastructure for safer production model releases.
Leaderboard Standings
Leaderboard Position Pending
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Assessment Highlights
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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
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Achievements
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About Details
Professional Bio
AI Engineer with expertise in multi-agent AI platforms, workflow orchestration, and LLM application development. Experienced in building production-ready RAG systems, MLOps pipelines, and automated reporting solutions using Python, FastAPI, and cloud technologies.
Executive Diploma Programme in Data Science & AI
IIIT Bangalore (Upgrad) (2023 - 2024)
Bachelor of Commerce in Banking & Insurance
Chaitanya Degree College (2019 - 2022)