Senior Solution Architect

🕒 June 25

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Sphera

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1989

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Sphera is a leading provider of enterprise sustainability management software, data, and consulting services. It offers solutions that enable organizations in sectors like Chemicals, Oil & Gas, Industrials, and Financial Services to manage their sustainability goals effectively. Sphera's offerings include the SpheraCloud platform, which focuses on Environment, Health, Safety & Sustainability (EHS&S) management, operational compliance, and risk management. The company's software and consulting services are designed to help organizations improve their safety, mitigate risks, reduce costs, and build resilience. By providing an integrated 360-degree view of sustainability and performance management, Sphera assists companies in meeting regulatory reporting requirements and achieving their sustainability objectives.

📋 Description

• Own and evolve the technical architecture for Sphera’s Corporate Sustainability and Environmental Accounting product areas • Define, document, justify, and communicate architectural decisions covering scalability, performance, security, and maintainability • Champion and embed an AI-Driven Development Lifecycle across requirements, design, implementation, testing, code review, documentation, and operational support • Define standards, guardrails, review gates, and policies for safe, secure, and compliant AI tooling use • Architect and deliver agentic AI capabilities from prototype through production • Design agentic systems using tool/function calling, orchestration, multi-agent patterns, retrieval-augmented generation, memory, context management, and human-in-the-loop controls • Own evaluation, testing, observability, latency, cost management, model selection, versioning, and graceful degradation for AI features • Address hallucination, grounding, prompt injection, data exfiltration, access control, auditability, and responsible AI risks • Contribute directly to the codebase and work daily with Claude Code and comparable agentic coding tools • Extend and tailor AI tooling through context files, custom commands, subagents, hooks, and MCP integrations • Provide technical guidance in .NET/C# or Node.js environments • Prototype and validate architectural approaches, especially in high-risk or uncertain areas • Partner with Product Management to translate requirements into technical designs and engineering outcomes • Support consistent, high-quality SaaS releases and resolve technical blockers and integration issues • Balance long-term architectural health with near-term delivery needs • Raise engineering capability through design reviews, pairing, mentoring, and coaching on AI-assisted engineering • Set standards for code quality, testing, observability, and security • Evaluate technical practices, reduce technical debt, and improve reliability and delivery speed • Act as the primary technical voice for the product area with internal stakeholders and customers where required • Maintain transparency about technical direction, risks, and trade-offs

🎯 Requirements

• 7+ years of software engineering experience • 3+ years in an architecture, lead engineer, or principal engineer capacity • Strong hands-on development experience in .NET/C# or Node.js • Proven experience architecting and delivering SaaS or enterprise software products at scale • Strong experience with Azure or AWS, distributed systems, and API design • Ability to translate product requirements into technical designs and execution • Experience mentoring engineers and influencing technical direction without direct authority • Demonstrable hands-on experience with Claude Code or equivalent agentic coding tools, used routinely on real production codebases • Practical experience operating within an AI-Driven Development Lifecycle across design, implementation, testing, review, and documentation • Working understanding of agentic AI patterns, including tool/function calling, orchestration, retrieval-augmented generation, and human-in-the-loop design • Working knowledge of the current LLM landscape and model-selection judgment • Experience defining evaluation, testing, and observability strategies for non-deterministic AI systems • Understanding of AI security and governance, including prompt injection, data leakage, access control, and responsible AI • Highly desirable technical proficiency with Databricks, SQL Server, and Azure SQL • Desirable experience shipping agentic AI solutions into production • Desirable experience with Model Context Protocol (MCP) or comparable standards • Desirable experience introducing AI tooling across an engineering organization • Comfortable in a fast-moving, low-formality, high-accountability environment • Strong communication skills with technical and non-technical stakeholders • Experience in global or cross-functional organizations is beneficial

🏖️ Benefits

• Equal Opportunity Employer committed to diversity and an inclusive environment