Full Stack Engineer & AI Systems
Akash Singh
4+ years designing high-throughput microservices, event-driven architectures, and production-grade AI systems, shipping scalable products across SaaS, communications, and industrial IoT.
About.
Software engineer with 4+ years of industry experience building across the full stack, from high-throughput backend microservices and distributed systems to responsive frontends and production-grade AI systems.
On the backend, I architect scalable microservices with Node.js, Django, and Python, with event-driven pipelines on Kafka, intelligent caching with Redis, and robust REST/GraphQL APIs backed by PostgreSQL and MongoDB. I care deeply about system design and building for failure.
In AI engineering, I ship production GenAI systems: RAG pipelines, conversational agents with NLP-driven SQL generation, and LLM integrations using LangChain and OpenAI, with a focus on accuracy, latency, and reliability at scale.
I treat observability as a first-class engineering concern. Distributed tracing, structured logging, SLO-based alerting, and Prometheus/Grafana dashboards are standard practice, not afterthoughts.
Full-Stack Development
End-to-end architecture from pixel-perfect frontends in React/Next.js to high-throughput backends in Node.js, Django, and PostgreSQL, optimized for performance and maintainability.
AI & GenAI Engineering
Shipping production GenAI systems: RAG pipelines, LLM-powered conversational agents, NLP-driven SQL generation, and sentiment analysis, with a focus on accuracy, latency, and reliability at scale.
Cloud & Infrastructure
Cloud-native deployments on AWS (EC2, ECS, Lambda, S3) with Docker, Kubernetes, and Terraform. Automated CI/CD pipelines, auto-scaling groups, and zero-downtime releases.
Observability & Reliability
End-to-end observability with Prometheus, Grafana, distributed tracing, structured logging, and SLO-driven alerting. Production systems are only as good as their monitoring.
Skills.
Languages, frameworks, infrastructure, and AI: the complete toolkit for building reliable, high-performance systems at scale.
Languages
Frameworks & Libraries
Databases & Messaging
Cloud & DevOps
Observability & Monitoring
System Design & Architecture
AI & ML Engineering
Experience.
4+ years building high-impact, production systems across SaaS, communications, and industrial IoT.
Petasense
Software Engineer
- Engineered a Spectrum Overlay feature for vibration analysis, enabling multi-signal comparison with real-time FFT rendering at 60fps using WebGL, cutting engineer analysis time by 60%.
- Designed a high-availability Interactive Annotations System using microservices, Redis caching, and RBAC, delivering sub-second response times, >99% uptime, and full audit logging.
- Built a GenAI-powered conversational analytics agent with LangChain, NLP-driven dynamic SQL generation, and multi-turn context memory, achieving 95% query accuracy and reducing data workflow time by 60%.
Exotel
Software Development Engineer
- Architected the frontend for the AMC (Automated Contact Center) product using Next.js, Turborepo monorepo, and Tailwind CSS, achieving 30% faster load times and a 25% improvement in user engagement metrics.
- Built an end-to-end speech intelligence service processing call recordings via OpenAI Whisper, delivering automated transcripts, summaries, and sentiment analysis using Node.js, Django, and Redis, improving NLP accuracy by 20%.
- Spearheaded GenAI integration into the contact center platform, delivering LLM-powered features including call summarization and intent detection, driving a 25% improvement in CSAT scores and shaping the company's AI product roadmap.
Cogno AI (Exotel)
Software Development Engineer
- Architected a distributed scheduler microservice with event-driven task queuing and intelligent retry logic, increasing scheduling efficiency by 66%, saving 110 engineering hours/week, and cutting operational costs by 20%.
- Deployed a WebRTC-based video conferencing solution using Django, WebSockets, and Dyte SDK, reducing video drop-off issues by 30% and boosting session engagement by 18%.
Cogno AI (Exotel)
SDE Intern
- Integrated Meta's Graph API to onboard Instagram and Facebook channels into LiveChat Fusion's Django backend, expanding platform reach, increasing customer interactions by 22%, and cutting average response time by 15%.
Projects.
Production-grade systems: distributed infrastructure, AI agents, observability platforms, and real-time applications.
Production-grade real-time messaging platform built on a micro-frontend architecture with Turborepo. Implements end-to-end encrypted WebSocket messaging, presence indicators, typing status, message reactions, and file sharing, with horizontal scaling via Redis pub/sub.
- Redis pub/sub enables horizontal scaling across nodes
- 30% faster builds via Turborepo monorepo caching
- Real-time presence, typing indicators & message reactions
- OAuth-backed auth with NextAuth and session management
CloudWatch · Infra Observability Dashboard
Full-Stack Monitoring & Alerting System
End-to-end observability platform that aggregates metrics, logs, and traces from distributed microservices into a unified real-time dashboard. Features custom Kafka-based ingestion pipelines, anomaly detection, threshold & ML-based alerting, and auto-discovery of service topology.
- Sub-second metric ingestion via high-throughput Kafka pipeline
- ML-based anomaly detection with configurable alerting
- Distributed tracing with correlation IDs across services
- Auto-discovery of service topology and dependency maps
GenAI Analytics Agent
aiConversational AI for Complex Datasets
AI-powered conversational agent enabling non-technical users to query industrial datasets in plain English. Combines NLP intent parsing, LangChain-driven dynamic SQL generation, Redis caching, and multi-turn context memory, deployed as a FastAPI microservice.
- 95% query accuracy on production industrial data
- 60% reduction in data analyst workflow time
- Multi-turn conversation with persistent session memory
Spectrum Overlay Engine
systemsHigh-Performance Signal Processing & Visualization
High-performance signal processing tool for vibration analysis in predictive maintenance. Engineers overlay multiple frequency spectrums on a single canvas, apply real-time FFT filters, zoom into anomalies, and export comparative reports, rendered at 60fps with WebGL acceleration.
- 60fps rendering via WebGL GPU acceleration
- 60% reduction in analysis time per engineer
- Real-time FFT computation and signal filtering
Self-hosted GitOps-style deployment platform that watches GitHub repos, builds Docker images in parallel, runs tests in isolated containers, and deploys to Kubernetes clusters, with automatic rollback on health check failure and full deployment audit trails.
- Zero-downtime rolling deployments to Kubernetes
- Automatic rollback triggered by health check failures
- Parallel build pipeline with layer caching
DistributedKV
distributedFault-Tolerant Distributed Key-Value Store
Fault-tolerant distributed key-value store built from scratch in Go, implementing the Raft consensus algorithm for strong consistency. Features consistent hashing with virtual nodes, automatic leader election, read replicas, and a custom binary wire protocol for low-latency inter-node RPC.
- Raft consensus guaranteeing strong consistency
- Consistent hashing with virtual nodes for even distribution
- < 2ms p99 read latency under load
Get In Touch
Let's build something great together
I'm always open to discussing new opportunities, interesting projects, or just connecting with fellow engineers.