{"id":4187774,"url":"https://alion.io/job/sigma-infosolutions-principal-architect-ai-and-full-stack","title":"Principal Architect - AI and Full Stack","company":{"id":2577091,"name":"Sigma Infosolutions","domain":"sigmainfo.net","url":"https://alion.io/company/sigmainfo","size_band":null,"is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Backend","role_family":"Backend","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Embeddings","optional":false},{"name":"GitOps","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Hybrid Search","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Node JS","optional":false},{"name":"Progressive Delivery","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"React.js","optional":false},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-11-12T18:35:10Z","employer_posted_date":null,"last_verified_at":"2026-11-12T18:35:10Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"We are looking for a strong hands-on, forward-thinking technical pioneer who can split their time between two critical mandates:\n\n50% Solution Architecture & Client-Facing Technical Engagement:\nArchitect scalable full-stack, cloud-native, AI-enabled, and multi-tenant solutions across client engagements, with strong focus on security, scalability, configurability, robustness, and long-term platform sustainability.\n\n50% AI Innovation & Strategic Growth:\nLead AI/GenAI POCs, define reusable AI capabilities, and establish modern AI-assisted and vibe coding-based engineering practices that enable rapid, continuous, and cost-effective delivery.\n\nKey Responsibilities:\n\nSolution Architecture & Technical Engagement (50%):\nArchitect scalable full-stack applications using React, Node.js, Python, Go, and modern cloud-native technologies.\nDesign and evolve multi-tenant/multi-brand SaaS architectures with strong tenant isolation and configuration-driven capabilities, minimizing tenant-specific custom development.\nEstablish reusable, configuration-driven architecture for UI, workflows, business rules, validations, integrations, permissions, feature flags, and tenant-specific requirements.\nDefine API-first, event-driven, microservices/modular architectures and integration patterns based on business and scalability requirements.\nGovern architecture quality and technical decisions, ensuring systems remain robust, scalable, secure, maintainable, and production-ready while supporting continuous onboarding of new tenant requirements.\nDefine vibe coding best practices covering requirement decomposition, architecture-first development, AI-assisted coding, context management, code review, testing, security validation, documentation, and human-in-the-loop governance.\nEstablish and govern code quality, engineering standards, architecture review, testing, security, and best-practice adherence across the complete development and deployment lifecycle.\nMaintain strong hands-on awareness of the complete development and deployment lifecycle and guide teams on design patterns, coding standards, technical debt reduction, DevOps, and cloud-native engineering practices.\nDefine modern deployment architectures using CI/CD, Infrastructure as Code, containers, Kubernetes, GitOps, automated testing, and progressive delivery.\nSupport solution planning, architecture reviews, pre-sales, and client-facing technical discussions.\nAct as a technical point of contact for quick customer/team handoffs, clarifications, and architectural alignment when required.\nCollaborate effectively with engineering and technology teams across different geographies and locations.\nMentor senior and mid-level engineers and conduct technical design and architecture reviews.\n\nAI Innovation, POCs & Practice Building (50%):\nArchitect and build AI/GenAI solutions including LLMs, model routing, embeddings, vector databases, hybrid search, RAG, tool/function calling, MCP, agent orchestration, guardrails, and AI observability.\nLead AI POCs from business use-case discovery and architecture through prototype, evaluation, integration, and production-readiness assessment.\nBring practical experience in implementing, deploying, and operationalizing AI/GenAI solutions in production environments.\nBuild reusable AI services and accelerators that can be consumed across multiple products, clients, and tenants rather than developing isolated project-specific solutions.\nDefine configuration-driven AI capabilities including tenant-specific models, prompts, tools, knowledge sources, policies, workflows, and AI features.\nDefine and govern the architecture of the semantic layer, ontology, knowledge representation, and related knowledge/semantic architecture required to support AI-enabled applications and intelligent workflows.\nDrive vibe coding-based application development and establish reusable agentic AI-assisted development workflows, templates, prompts, skills, coding agents, and engineering accelerators.\nIdentify opportunities to use AI agents across the SDLC, including requirement analysis, architecture, coding, code review, testing, debugging, documentation, migration, and DevOps automation.\nIdentify opportunities to apply AI to improve engineering productivity, automate business processes, reduce operational overhead, and create new client-facing capabilities.\nCollaborate with leadership to define the AI technology roadmap, reusable accelerators, reference architectures, and AI Center of Excellence capabilities.\nTrack emerging AI technologies and evaluate their applicability across client engagements and industry-specific use cases.\n\nAdditional Responsibilities:\nIdentify business opportunities for modernization, platform reuse, AI-led engineering transformation, account expansion, and new AI-enabled business solutions.\nConduct internal workshops, guide upskilling plans, and help build a pipeline of AI-savvy engineers.\nParticipate in marketing and sales enablement, including client demos, case studies, and proposal support.\nSkills\nAI, Architecture, Full-Stack, Gen AI, Go, LLM, Node.js, 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