Satyam Naolekar

Software Engineer

Bengaluru, Karnataka, India15 yrs 3 mos experience

Highly StableAI Enabled

Key Highlights

Expert in Video Intelligence and AI Infrastructure.
Led design of low-latency multimodal systems.
Awarded Microsoft Accountability Award for collaboration.

Stackforce AI infers this person is a highly skilled engineer in AI and Video Intelligence for enterprise solutions.

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Skills

Core Skills

Video IntelligenceDistributed Systems ArchitectureAi InfrastructureEmbedded SystemsSoftware Engineering

Other Skills

AlgorithmsAndroid DevelopmentAngularJSApacheAudio-Video ProcessingBoost C++BootstrapC++CSSConflict-Resolution LogicDatabasesDistributed State SystemsEJBEclipseFfmpeg

About

Staff Systems Engineer specializing in Video Intelligence, AI Infrastructure, and Distributed Systems. With over 13 years of experience, including 7 years at Microsoft and an M.S. from IIT Delhi, I architect the high-performance platforms required to translate raw multimedia signals into scalable digital intelligence. My work focuses on the engineering gap between research and production: leading the design of low-latency multimodal systems (LLMs/RAG), real-time computer vision at the edge, and the resilient distributed state orchestration that underpins global-scale collaboration. Core Focus: • Video Intelligence • Edge AI • Distributed Systems Architecture • Multimodal LLM Orchestration

Experience

Nouveau labs

Staff Engineer

Dec 2024 – Dec 2025 · 1 yr · Bengaluru, Karnataka, India · Hybrid

Engineered a Multimodal AI Orchestration Layer integrating LLMs and RAG (Retrieval-Augmented Generation) to drive context-aware PSTN voice interactions with human-like responsiveness.
Optimized Real-Time Conversational Flow by implementing a dual-layer VAD (Voice Activity Detection) system and Google Chirp-3 (STT/TTS), achieving millisecond-precise turn-detection and interrupt handling.
Enhanced Jitsi VideoBridge (JVB) Infrastructure: Modernized the Java/Kotlin media pipeline to support advanced enterprise features, including breakout rooms, server-side call transfers, and synchronized multi-user recording.
Designed a Scalable Recording & Post-Processing Engine: Built a service-based architecture coordinating via HTTP/WebSockets to handle A/V stitching, alignment, and adaptive distribution across varied network conditions.
Deployed Real-Time Transcription & Intelligence: Integrated Gladia and Google Speech V2 into Jigasi for live transcription; built downstream NLP pipelines for emotion analysis and automated meeting summaries for participant approval.
Engineered High-Throughput AI Ingestion: Developed the bridging logic to stream high-bitrate media from JVB into inference engines, enabling real-time analytics without compromising bridge stability or latency

Multimodal AI OrchestrationVoice Activity DetectionJavaKotlinHTTP/WebSocketsReal-Time Transcription+3

Microsoft

SDE II – Microsoft Project, Office 365 Group (Project / Planner / Teams)

Jan 2018 – Dec 2024 · 6 yrs 11 mos · Hyderabad, Telangana, India · Hybrid

Engineered Distributed State Systems: Collaborated with a senior engineering team to deliver the end-to-end multi-user Undo/Redo framework for Project for the Web. Focused on the server-side orchestration and conflict-resolution logic required for reliable real-time co-authoring.
Core Engine Modernization: Contributed to the transition of the C++ Scheduling Engine to a cloud-first architecture, driving improvements in performance, memory efficiency, and system observability for global enterprise deployments.
AI-Driven Feature Development: Developed and integrated LLM/GPT-based capabilities within the Project ecosystem to automate complex scheduling workflows and enhance data synthesis.
Media Infrastructure (Teams Together Mode): Conceptualized and prototyped a high-efficiency server-side recording solution for Microsoft Teams during a global hackathon, focusing on optimized layout rendering.
Technical Knowledge Leadership: Served as a Subject Matter Expert for the Undo/Redo system, conducting technical deep-dives at Microsoft Headquarters (Redmond) regarding the system’s design and implementation.
Honors: Awarded the Microsoft Accountability Award for cross-team collaboration and the successful delivery of critical co-authoring infrastructure

Distributed State SystemsC++LLM/GPT IntegrationServer-Side OrchestrationConflict-Resolution LogicDistributed Systems Architecture+1

Impartus innovations

Sr. Software Engineer

Dec 2014 – Dec 2017 · 3 yrs · Bengaluru Area, India · On-site

Designed and built the core multimedia capture and processing system for the product, responsible for end-to-end collection, packaging, and preparation of audio-video content.
Developed a C++ recording module deployed on Raspberry Pi devices to capture classroom content locally, ensuring zero data loss during network glitches and enabling reliable offline-first recording.
Implemented scheduled, resilient transfer workflows to sync recordings from edge devices to the college’s central media processor for heavy post-processing and transformation.
Created scalable media tools and pipeline components used across multiple product modules, solving several previously unsolved challenges in video ingestion, content integrity, and synchronization.
Contributed across the entire stack—from hardware integration and OS-level optimization, to shell automation, backend services, and web-facing components—to enhance product scalability and robustness.

C++Multimedia CaptureAudio-Video ProcessingRaspberry PiShell AutomationEmbedded Systems+1

Oracle

2 roles

Senior Software Engineer

Promoted

Mar 2014 – Nov 2014 · 8 mos · Hyderabad Area, India

Design, develop and maintain the java-based Oracle Application Framework (OAF), which is responsible for application design in the other products of the corporation.
Design and develop library for enhance user experience of enterprise web pages on touch devices.
Integration of library in the Oracle Application Framework (OAF).

JavaOracle Application FrameworkWeb DevelopmentSoftware Engineering

Software Engineer

Aug 2012 – Mar 2014 · 1 yr 7 mos · Hyderabad Area, India

Iit delhi | research associate

MSR video compression

Jul 2010 – Nov 2012 · 2 yrs 4 mos · New Delhi Area, India

Research Associate in project titled “Parametric video compression techniques”, sponsored by STMicroelectronics.
Designed and developed advanced motion estimation algorithms for high-resolution video compression.
Integrated new algorithms into standard codec reference implementations, including HEVC (HM) and H.264 (JM).
Evaluated algorithmic performance against standard motion estimation methods, focusing on compression efficiency, speed, and quality trade-offs.
Contributed to research on optimized video compression pipelines targeting next-generation multimedia systems.

Motion EstimationVideo CompressionHEVCH.264Video Intelligence