Senior Technical Lead

Technical Leadership • Lead and mentor a cross-functional engineering team (5–7 engineers), ensuring high standards in code quality and delivery • Own backend architecture, system design, and engineering roadmap • Drive end-to-end design, development, and deployment of scalable systems • Conduct code reviews, enforce best practices, and resolve complex technical challenges • Drive internal R&D initiatives in GenAI, automation, and scalable cloud solutions Backend Engineering • Design and build high-performance, scalable, and secure REST APIs using FastAPI • Develop microservices and distributed systems with fault tolerance and resiliency • Optimize systems for latency, scalability, and reliability • Implement best practices for: o Performance optimization o Security o Testing (unit/integration) o Observability (logging, metrics, tracing) Cloud & DevOps (Azure) • Architect and deploy cloud-native solutions using: o Compute: Azure App Services, Container Apps, AKS, Azure Functions o Data: Azure SQL, Cosmos DB, Storage Accounts o Monitoring: Application Insights, Log Analytics • Build and manage CI/CD pipelines using Azure DevOps • Implement Infrastructure-as-Code using Terraform (preferred) or Bicep • Ensure: o High availability and fault tolerance o Monitoring, alerting, and observability o Cost optimization and governance Client & Stakeholder Management • Act as the primary technical point of contact for internal clients • Lead technical discussions, solution design workshops, and architecture reviews • Translate business requirements into scalable technical solutions • Communicate risks, trade-offs, and progress effectively • Present technical concepts clearly to both technical and non-technical stakeholders Generative AI (Preferred) • Design and implement RAG-based architecture and LLM-powered services • Work with: o Azure OpenAI / OpenAI APIs o Vector databases (e.g., Azure AI Search) • Build production-grade GenAI applications focusing on scalability, latency, and security • Evaluate and integrate emerging AI technologies into client solutions Leadership & Soft Skills • Communication: Clearly explains technical decisions, trade-offs, and risks; leads client discussions confidently • Team Leadership: Mentors engineers, provides actionable feedback, and maintains high engineering standards • Ownership: Takes end-to-end responsibility for delivery, production issues, and system quality • Decision-Making: Makes sound technical decisions under ambiguity, balancing short-term needs and long-term design • Execution: Drives predictable delivery, proactively manages risks, and ensures high-quality outcomes • Collaboration: Works effectively across engineering, product, and business teams • Adaptability: Quickly learns, adopts new technologies (especially GenAI), and drives continuous improvement

8–12 years in core software development, distributed systems, or large-scale platform engineering - including strong Python and Nodejs expertise. • 4-5 years building, deploying, and scaling machine learning models, LLMs, or agentic workflows into live production. • Deep experience with FastAPI (or similar modern frameworks) • Hands-on experience with Azure cloud architecture and operations • Strong knowledge of: o Microservices and distributed systems o Docker and Kubernetes (ACA and AKS) • Proven experience with: o CI/CD pipelines (Azure DevOps) o Infrastructure as Code (Terraform preferred) • Demonstrated leadership experience in mentoring teams and driving delivery Preferred Skills • Experience with Azure AI foundry, Databricks, or big data pipelines • Knowledge of event-driven systems (Azure Service Bus, Azure Data Factory) • Familiarity with API gateways and service mesh • Understanding of cloud security, IAM, and governance