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Technical Architect

🗓️ Posted 2026-08-15 India Full-time Hybrid ICT

Company shared salary

Market rate

₹120,000–₹250,000/mo (₹1,440,000–₹3,000,000/yr)

Based on similar roles (title + domain + location).

About the Company

At Viamagus, every engineer works with AI every day - not as a side experiment, but as the core of how we build. We're looking for a Technical Architect who has shipped real systems, led real teams, and already treats AI tools as first-class instruments of engineering. You'll own architecture across all client engagements, mentor a team of 15-20 engineers, and shape how an AI-native consultancy delivers at scale.

Responsibilities

● Design scalable, secure architectures for client engagements and lead technical due diligence on proposals
● Drive production readiness: incident management, observability, release processes
● Mentor backend, mobile, and cloud engineers - through architecture reviews, code reviews, and retrospectives
● Be the technical face to client CTOs: translate business objectives into architecture decisions and escalate risks with proposed mitigations
● Enforce security-first design including threat modelling, data classification, and AI-specific risks (prompt injection, PII leakage)
● Ensure compliance readiness for ISO 27001, SOC 2, and HIPAA where applicable
● 8+ years of software development, 3+ years in an architect or lead role; degree in CS/Engineering (Master's preferred)
● Built and owned systems from scratch to production - full lifecycle, not slices
● Multiple integration experiences: third-party APIs, enterprise systems (SAP, Salesforce, ERP), messaging buses, legacy modernisation
● Built reusable platforms, SDKs, and internal tooling adopted across teams
● Technology-agnostic: strong in at least one modern backend stack, one frontend framework, and one cloud platform
● AWS or Azure architecture: VPC design, IAM, container orchestration, cost optimisation
● DevOps fluency: Docker, Jenkins/GitHub Actions, Terraform or CDK
● Performance tuning, distributed tracing, APM tools (Datadog, New Relic, or equivalent)
● AppSec fundamentals: OWASP Top 10, VAPT remediation, secrets management; ISO/SOC 2/HIPAA exposure a plus
● Daily use of AI coding tools - Claude Code, Cursor, Copilot, or equivalent - and the ability to articulate where they help and where they fall short
● LLM integration patterns: OpenAI, Anthropic, Gemini, or open-source models; streaming, function calling, structured outputs
● RAG fundamentals: vector DBs (pgvector, Pinecone, Qdrant), embeddings, chunking, retrieval tradeoffs
● Agentic systems: tool use, multi-step agents, LangGraph or CrewAI
● Prompt engineering: versioning, structured outputs, guardrails, handling hallucinations
● AI evaluation and cost awareness: measuring quality, latency, and cost of LLM-powered features
● MCP (Model Context Protocol): awareness of what it is and where it fits
● Open-source contributions or published AI tooling
● Real-time sync experience: CRDTs, Realm, Ditto, or offline-first architectures
● Technical writing - blogs, conference talks, or public GitHub work
● Google, AWS, or Azure certifications (a bonus, not a substitute for depth)