Jobs at Flyte Solutions Ltd.

Leads architecture, design, and implementation of enterprise-scale backend platforms using Python. Responsibilities include developing APIs and distributed systems, guiding engineering teams, conducting code reviews, establishing security and performance standards, supporting cloud deployments and CI/CD, resolving technical risks, mentoring developers, and communicating technical decisions to stakeholders. The role also involves technical leadership, architecture governance, production support, and integrating cloud, AI/ML, and emerging technologies.

Develop and maintain enterprise web applications across the full software development lifecycle. Build .NET backend services, APIs, business logic, responsive frontend applications, and database solutions. Responsibilities include testing, debugging, code reviews, performance optimization, third-party integrations, deployment, production support, documentation, and Agile/Scrum collaboration. The role requires strong software engineering practices, secure and scalable coding, technical solution design, and teamwork with analysts, designers, QA, and DevOps professionals.

Manage AWS and GCP infrastructure, Kubernetes/EKS clusters, Docker applications, Terraform IaC, and CI/CD pipelines. Handle cloud networking, IAM, security, storage, monitoring, logging, multi-environment deployments, incident response, root-cause analysis, and service recovery. Automate operations with Shell, Ansible, and Packer while collaborating across engineering and operations teams and maintaining technical documentation and runbooks.

Leads enterprise infrastructure, cloud operations, platform reliability, modernization, security resilience, automation, and FinOps initiatives. Oversees AWS, Azure, and/or Google Cloud environments, infrastructure architecture, DevOps, SRE, IaC, observability, incident management, disaster recovery, vendor relationships, budgets, and service providers. Develops infrastructure strategy and technology roadmaps while managing and mentoring engineering teams and communicating risks, performance, and investment needs to senior stakeholders.

Lead the architecture, development, and production deployment of enterprise Generative AI platforms and applications. Design scalable RAG pipelines, multi-agent workflows, copilots, conversational BI, and AI assistants. Establish LLMOps, evaluation, observability, guardrails, governance, and security practices. Optimize inference performance, cost, reliability, and scalability while evaluating emerging AI technologies. Mentor engineers, provide technical leadership, and partner with stakeholders to deliver production-grade AI solutions.

Design, build, and maintain high-performance Python backend systems, RESTful APIs, and microservices. Integrate databases and third-party services, collaborate with cross-functional teams, contribute to CI/CD and DevOps, perform code reviews, debugging, performance tuning, and production support.

Design, develop, and deploy scalable, production-ready AI platforms and services using LLMs, RAG, agentic AI, and vector search. Build backend APIs and microservices, orchestrate AI workflows, integrate AI into enterprise systems, optimize model performance, and collaborate across teams to deliver enterprise AI solutions.