Senior Technical Lead

Job Summary

highly skilled Technical Lead to build and scale cloud-native backend systems on Azure. This role combines hands-on engineering, technical leadership, and innovation in Generative AI to deliver high-impact solutions for global clients.
The ideal candidate is a proactive leader who can balance deep technical expertise with team leadership, drive architectural decisions, and ensure high-quality delivery while collaborating with internal and external stakeholders.

Key Responsibilities

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

Skill Requirements

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

Other Requirements

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