Job Summary
As a Staff Software Engineer, you’ll design, develop, and optimize back-end services within a distributed microservices ecosystem. You'll have major hands-on development along with architectural decisions, collaborate with cross-functional teams, and mentor engineers to deliver high-impact solutions. You’ll work on core systems that integrate machine learning models, optimize AI pipelines, and deliver real-time insights for software automation platform.
Key Responsibilities
Design & Development
- Build Scalable Microservices : Architect and develop secure, resilient microservices using Python to handle high-throughput workloads, ensuring compliance with best practices for scalability and fault tolerance.
- Multimedia Stream Processing : Design services to ingest, process, and analyze multimedia streams (images, video) with sub-second latency , leveraging tools like FFmpeg, OpenCV, or GStreamer for real-time operations.
- Cloud-Native Deployment : Deploy and manage services on AWS / GCP / Azure using Docker / Kubernetes , optimizing for cost, performance, and scalability in containerized environments.
- Optimize APIs & Databases : Develop event-driven APIs (REST / gRPC) for seamless integration and optimize SQL / NoSQL databases (PostgreSQL, Cassandra, Redis) for high concurrency and low-latency queries.
- AI / ML Workflow Orchestration : Design and deploy microservices to automate AI / ML pipelines (training, inference, monitoring)
- System Design Leadership : Drive architectural decisions to ensure scalability, security, and resilience across distributed systems, including disaster recovery, load balancing, and data encryption strategies
Scalable Infrastructure
Cloud-Native Architecture : Deploy and manage services on AWS / GCP / Azure using Kubernetes (EKS, GKE, AKS) to optimize cost, scalability, and geographic redundancy.Containerization & Orchestration : Design Docker / Kubernetes -based workflows for seamless scaling of multimedia processing, AI / ML and other workloads.CI / CD Pipelines : Implement robust GitHub Actions / ArgoCD workflows for zero-downtime deployments, automated testing, and rollback strategies.Resilient Data Systems : Optimize SQL / NoSQL databases (PostgreSQL, MongoDB) and real-time data layers (Kafka, Redis) for high-throughput multimedia workloads and AI inference results.Security & Compliance : Enforce encryption (TLS, AES-256), IAM policies, and audit trails for configuration data across hybrid-cloud environments.Edge & Hybrid Deployments : Architect solutions for edge computing to reduce latency in video processing and AI inference.Observability & Performance :
Troubleshoot issues, enhance performance, and implement monitoring (Prometheus, Grafana) for system observability.Implement distributed tracing using Open Telemetry for monitoring distributed services.Collaboration & Leadership :
Collaboration : Partner with Product, Front-End, DevOps, and QA teams in Agile / Scrum workflows to deliver end-to-end solutions.Leadership : Mentor engineers on best practices for real-time systems and establish coding best practices and conduct rigorous code reviewsQualifications
Education :
BE / MTech in Computer Science or equivalent branch.Experience :
8+ years of relevant experienceProven work with distributed systems, microservices, and high-traffic environmentsTechnical Skills :
Languages : Python, Go, JavaScript / TypeScript.Cloud & Tools : AWS / GCP / Azure, Docker, Kubernetes, Kafka / RabbitMQ / RedisDatabases : PostgreSQL, MongoDB, Redis.DevOps : Kubernetes, Docker, Terraform, CI / CD pipelines (Jenkins, ArgoCD, GitHub Actions).Video Tools : FFmpeg, GStreamer, WebRTC, RTSP / RTMP protocols.Protocols : REST, gRPC, WebRTC, RTSP, WebsocketsSoft Skills :
Strong problem-solving, communication, and leadership abilities.Strong collaboration skills with cross-functional AI / Product teams.Ability to translate complex AI concepts into scalable engineering solutions.Preferred Qualifications
Contributions to open-source projects.Certifications in cloud technologies (AWS / GCP).Expertise in performance tuning, security, or advanced system design.Experience with edge computing for video processingFamiliarity with APMs and Cloud monitoring services such as DataDog