Software Architect (Backend-focused)

We are looking for an experienced Software Architect to lead the design and evolution of various backend systems for our clients' platforms. This is a client-facing technical leadership role where you will work across multiple projects and stakeholders, translating client requirements into technical solutions that hold up in production.

While the primary focus is backend architecture, the role also requires good working knowledge of cloud infrastructure and security, since backend design decisions now shape deployment and security choices too. Frontend is not part of the core responsibilities, but familiarity with how backend design decisions affect frontend integration is expected. Increasingly, client projects call for backend systems that incorporate AI/LLM-powered features (chat interfaces, retrieval-augmented generation, copilots, automation). You will be expected to architect these components with the same rigor as any other backend service, covering data pipelines, APIs, security, and scalability, rather than treating them as a separate discipline.

Responsibilities

• Design and own end-to-end backend architecture (APIs, services, data models, and integration patterns) for client projects of varying scale and complexity
• Define and evolve architectural patterns (microservices, modular monoliths, event-driven architecture, API-first design) appropriate to each client's context and constraints
• Translate business and functional requirements from clients into technical designs, estimates, and delivery plans
• Design cloud-native and containerized solutions (Kubernetes, Docker) across major cloud providers (AWS, Azure, GCP), including hybrid and multi-cloud scenarios where relevant
• Build security into the architecture from day one: authentication/authorization (OAuth2/OIDC), secrets and identity management, data protection, and alignment with standards such as OWASP
• Define and govern API contracts, integration standards, and data flow between services and external systems
• Guide and mentor development teams on architectural decisions, design patterns, coding standards, and technical debt management
• Assess feasibility and trade-offs of proposed solutions and explain them clearly to technical and business stakeholders
• Participate in pre-sales and proposal activities: contribute architecture sections, technical estimates, and solution design for client-facing bids and technical audiences
• Design and integrate AI/LLM-powered capabilities into backend systems - including retrieval-augmented generation (RAG) pipelines, vector search, prompt/response handling, and integration with LLM providers or self-hosted models
• Define data architecture for AI use cases: ingestion, chunking, embedding, and retrieval pipelines, along with the data governance and access controls around them
• Evaluate build-vs-buy and vendor decisions for AI tooling (LLM APIs, vector databases, orchestration frameworks) based on client requirements, cost, and data sensitivity
• Apply security and compliance thinking specific to AI systems: data leakage risks, prompt injection, access control on retrieved content, and responsible handling of client data used in AI pipelines

Skills & Experience

• Hands-on backend software development experience, with at least 2-3 years in an architect or technical lead capacity
• Bachelor's or master's degree in computer science, engineering, or a related field (or equivalent professional experience)
• Strong command of at least one major backend ecosystem (e.g., Java/Spring, .NET, or Python) and the ability to reason across others
• Solid experience designing distributed systems, RESTful and/or event-driven APIs, and data models (relational and NoSQL)
• Practical experience with cloud platforms (AWS and/or Azure) and cloud-native architecture (containers, orchestration)
• Working knowledge of application and infrastructure security principles
• Understanding of non-functional requirements: scalability, availability, performance, and resilience/failover design
• Working understanding of LLM-based architectures: how RAG pipelines, embeddings, and vector search fit into a backend system, and how to integrate LLM APIs or self-hosted models into production services
• Ability to assess, explain and draw existing systems and propose plans for incremental migration or rewriting
• Strong communication and documentation skills (able to explain architectural decisions to both engineers and business/client stakeholders)
• Comfortable working directly with clients: requirements gathering, technical workshops, and presenting solutions to steering committees or non-technical audiences
• Willingness to travel to customer sites and events as required

Nice to Have

• Exposure to frontend architecture (React, Angular, or similar) sufficient to guide full-stack integration decisions, even if not hands-on
• Familiarity with security-specific tooling or practices: penetration testing basics, vulnerability scanning, or compliance frameworks (ISO 27001, SOC 2, GDPR-related technical controls)
• Hands-on experience building or productionizing RAG systems, agentic workflows, or AI copilots
• Familiarity with vector databases and embedding models
• Understanding of LLM evaluation, guardrails, and cost/latency optimization for production AI features
• Experience fine-tuning or self-hosting open-weight models for cost or data-sensitive client environments
• Prior involvement in technical pre-sales, RFP responses, or solution architecture for client proposals
• Experience mentoring or leading distributed/remote development teams

Apply now!

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