Technical Architect
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Job Description
Technical Architecture & Delivery
Education
- Own technical architecture decisions on delivery engagements — designing component-level solutions that align with broader architecture blueprints defined by the Solution or Principal Architect.
- Actively participate in engineering delivery, bridging the gap between architectural intent and implementation — reviewing code, driving technical design sessions, and unblocking development teams.
- Ensure technical quality across deliverables — conducting architecture and code reviews, validating implementation against design standards, and driving resolution of technical debt.
- Manage technical risk on delivery projects and escalate architectural concerns to the Solution Architect.
- Learn, implement, and advocate for AI-native engineering practices — including GenAI integration patterns, agentic workflows, and intelligent automation — within delivery teams.
- Contribute to the development and maintenance of AI engineering frameworks, solution accelerators, and reusable technical assets.
- Evaluate and experiment with new tools, APIs, and platforms in the AI and cloud-native space — bringing relevant innovations into delivery practice.
- Engage with client technical teams to understand system landscapes, integration requirements, and technical constraints.
- Propose pragmatic, technology-forward solutions to complex engineering challenges across application modernization, AI integration, and cloud migration.
- Support the Solution and Principal Architect in pre-sales activities including technical assessments, proof-of-concept design, and effort estimation.
- Design and implement cloud-native architectures on AWS, Azure, or GCP — including containerization (Kubernetes/Docker), serverless functions, and event-driven patterns.
- Implement intelligent automation components using workflow engines, RPA tools, or custom AI-driven pipelines.
- Mentor senior engineers and developers — supporting technical upskilling on AI tools, cloud platforms, and modern engineering practices.
- Contribute to Jade's internal community of practice through knowledge sharing, documentation, and participation in architecture discussions.
Education
- Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related technical field is required.
- 5–9 years of total experience in software engineering, with at least 2–3 years in a technical architecture, lead engineer, or tech lead role.
- Hands-on experience building and delivering enterprise-grade solutions across cloud, AI/ML, and application engineering.
- Experience working in client-facing delivery environments within IT services or consulting organizations is preferred.
- Engineering Stack: Strong hands-on proficiency in .NET (C#, ASP.NET Core) and/or OpenSource stacks (Python, Java, Node.js). Experience across both stacks is a strong advantage.
- AI & GenAI: Practical exposure to Generative AI integration, LLM APIs (OpenAI, Azure OpenAI), LangChain, RAG patterns, or agentic workflow frameworks.
- Cloud: Hands-on experience with AWS, Azure, or GCP — microservices, containers (Docker/Kubernetes), serverless, and CI/CD pipelines (GitHub Actions, Azure DevOps).
- Intelligent Automation: Exposure to RPA tools, workflow orchestration engines, or AI-driven automation platforms.
- Enterprise Platforms: Familiarity with Oracle, SAP, Salesforce, or ServiceNow is a plus.
- Cloud Certification (any level — AWS, Azure, or GCP) is a plus.
- Strong technical communication — able to explain architecture decisions clearly to engineering teams and non-technical stakeholders.
- Delivery-focused and hands-on — willing to roll up sleeves and contribute to implementation alongside leading architectural decisions.
- Curious and self-motivated — proactively explores new AI tools, frameworks, and engineering patterns.
- Collaborative team player — works effectively in onshore-offshore delivery models across time zones.
More Info
Key Skills
ASP.NET Core
Azure OpenAI
GitHub Actions
LLM APIs
LangChain
Generative AI
RAG patterns
serverless
AI-driven automation platforms
OpenAI
workflow orchestration engines
Containers
About Company
Skills:
Version Control Systems, Docker, APEX, Performance Monitoring, Salesforce Development Lifecycle, DevOps tools and technologies, Lightning Web Components, Salesforce product suite
Skills:
Sas Macros, Spark SQL, Pyspark, Azure Databricks, Sas Enterprise Guide, Proc Sql, Base Sas, Databricks, Python, SAS datasets libraries and file processing, Production support and troubleshooting, Medallion Architecture Bronze Silver Gold, SAS DATA Step, Databricks Lakehouse, Unity Catalog, Understanding of SAS business logic and data lineage, Performance tuning and optimisation, SAS Viya, Delta Lake, CI CD and Git-based development, Batch scheduling and job dependencies, SAS Grid, Databricks Workflows
Skills:
.NET, Asp.net Mvc, CSS, HTML, Javascript, Iis, Agile, Scrum, Sql
Skills:
GCP certifications or demonstrated GCP production experience (Cloud Run, GKE), PostgreSQL, Node.js, Datadog, Redis, Angular, New Relic, React, Typescript, MongoDB, Nestjs, BigQuery, Telemetry monitoring, OpenTelemetry, API gateway design, Microservices patterns, Pub/Sub, ML integration, Ai, Salesforce ecosystem and integrations, Backend and system architecture, Event-driven architectures
Skills:
containerization , Orchestration, Graphql, Node.JS, Microservices, Typescript, Gcp, Javascript, Azure, AWS, Next.JS, Backbone.JS