Jobs at SoftTech Engineers Limited

Leads a full-stack product revamp by evaluating architecture, defining technical strategy and roadmap, and improving scalability, performance, and maintainability. Collaborates with product, QA, UX/UI, and other stakeholders to align engineering initiatives with business objectives. Provides technical leadership, mentorship, recruiting, onboarding, delivery process improvement, KPI definition, and adoption of cloud, AI-assisted development, and engineering productivity tools.

Leads end-to-end statewide solution implementation, including schedules, rollouts, stakeholder and vendor coordination, requirements, testing, releases, production support, integrations, training, risk management, SLA tracking, reporting, and milestone-based customer approvals. Oversees onsite and offshore teams, coordinates defect resolution and root cause analysis, and ensures compliance with security and audit requirements.

Design, develop, and maintain scalable web applications using C#, .NET Core, ASP.NET Core, MVC, and REST APIs. Architect microservices-based solutions, design and optimize SQL Server databases, and use Entity Framework Core for data access and performance tuning. Collaborate with product, QA, and UI/UX teams to deliver secure, maintainable solutions.

Designs, implements, and manages Azure DevOps CI/CD and database pipelines for enterprise .NET, C#, and React applications. Builds development infrastructure, automates release processes, deploys Docker and Kubernetes workloads on AKS, manages Git repositories and branching strategies, and monitors applications using Azure tools. The role also involves security implementation with Key Vault, RBAC, and Defender for Cloud, production root-cause analysis, troubleshooting, and deployment of updates and fixes.

Develop and deliver AI-powered products using generative AI, LLMs, prompt engineering, fine-tuning, RAG, and machine learning techniques. Build scalable web and backend applications with Python frameworks, integrating SQL and NoSQL databases. Apply NLP, deep learning, predictive modeling, and data science methods across customer-facing SaaS and cloud-based products. Collaborate in a fast-paced environment while demonstrating strategic thinking, problem-solving, leadership, and continuous learning.

Lead and build a cross-functional full-stack engineering team while remaining hands-on in backend and frontend development. The role owns delivery, system architecture, coding standards, technical guidance, hiring, coaching, testing, code quality, and collaboration with engineering teams. Responsibilities include developing scalable microservices, REST APIs, CI/CD and DevOps practices, and sustainable engineering processes supporting the energy transition.

Lead the AI strategy, architecture, development, and deployment of scalable AI-powered Metaverse products. Build LLM applications, agents, copilots, RAG systems, and transformer-based models while guiding model evaluation, governance, security, responsible AI, cloud deployment, and MLOps. Collaborate across product, engineering, UX, BIM, CAD/CAE, digital twin, and Metaverse teams. Mentor AI engineering and data science teams, manage stakeholders, and deliver enterprise-scale solutions.

Lead architecture and hands-on development of scalable, cloud-native full-stack applications using .NET Core, C#, React.js, and Azure DevOps. Design REST APIs, microservices, and distributed systems while driving scalability, security, performance, and reliability. Contribute to machine learning, digital twin, data pipeline, model deployment, and MLOps initiatives. Mentor engineers, review technical work, collaborate with stakeholders, and support delivery planning, estimation, and technical risk management.

Lead the architecture, design, and hands-on development of scalable full-stack cloud-native applications using .NET Core, C#, React.js, Azure, REST APIs, microservices, and distributed systems. Establish technical standards, review code, optimize performance and security, and mentor engineers. The role also supports AI/ML integration, Digital Twin architectures, data pipelines, model deployment, MLOps, stakeholder collaboration, delivery planning, and technical risk management.