Technical Specialist

Job Summary

We are looking for a 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

• 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

Skill Requirements

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

Other Requirements

Good to have :

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