Senior Solutions Architect

Job Description: Solution Architect - Agentic AI Platform

This role will be responsible for partnering with client stakeholders at the board and executive levels to translate complex business challenges into production-ready autonomous agentic architectures. You will own the technical relationship during the discovery phase, blueprint the core reference architectures, and guide our internal engineering pods through successful implementation.

Key Responsibilities

• Solution Architecture & Technical Blueprinting
• Design and document standardized, enterprise-grade Reference Architectures for multi-agent orchestration and advanced Retrieval-Augmented Generation (RAG) systems using the Claude Code or Gemini Enterprise Agent Platform.
• Blueprint end-to-end "Agentic Workflows," mapping out how multi-turn reasoning, persistent memory, and state management will behave in live environments.
• Build reusable architecture scaffolds and integration patterns that allow developers to connect agents to core enterprise systems (e.g., Splunk, Elastic, ServiceNow, Salesforce and custom telemetry stacks).
• Transition seamlessly from abstract whiteboard designs to concrete implementation by writing core foundational code, configuration scripts, or orchestration loops alongside the engineering team.
• Act as the technical bridge between Softility’s delivery teams and Google Cloud's partner engineering group to unblock platform-level execution barriers.
• Tactical Pre-Sales & Consultative Engagement
• Act as the primary technical authority during high-touch, pre-sales discovery workshops to discover, define, and scope client use cases.
• Conduct highly technical product demonstrations and deliver deep-dive sessions to client engineering teams, effectively neutralizing competitive technologies (e.g., OpenAI Assistants, AWS Bedrock).
• Model Optimization & Workload Selection
• Evaluate enterprise tasks to select the optimal model configuration, balancing computational efficiency and accuracy.
• Define token budget management strategies and performance caching layers to ensure client systems scale effectively.
• Design benchmarking metrics to continually evaluate agent precision, grounding scores, and execution latency.
• Security, Compliance & Semantic Governance
• Oversee absolute security compliance for all agent deployments, ensuring architectures adhere to Zero-Trust standards and strict data residency mandates.
• Design and implement Semantic Governance Layers to enforce safety guidelines, prevent hallucinations, and automate PII masking before data reaches foundational model layers.

Required Technical Experience & Qualifications

• Cloud Expertise (preferably GCP): Deep architectural knowledge of Google Cloud Vertex AI (Agent Platform), BigQuery, VPC Service Controls, and IAM security frameworks. Holding a Google Cloud Professional Cloud Architect or Professional Machine Learning Engineer certification is highly preferred.
• Agentic Frameworks & AI Tooling: Proven experience building production-level autonomous systems utilizing the Gemini ADK, LangChain, or comparable agentic libraries.
• Backend Mastery: Exceptional proficiency in Python or Node.js, combined with deep familiarity with API design, enterprise webhooks, and asynchronous message queues.
• Modern Integration Standards: Direct experience working with enterprise application API architectures (REST, gRPC) for platforms like Salesforce, ServiceNow, or large-scale Observability stacks.
• System Observability: Familiarity with OpenTelemetry (OTel), logging fabrics, and monitoring frameworks to track agent behavior in production environments.
• Enterprise Software Delivery: Strong experience in modern DevOps methodologies, including infrastructure-as-code (Terraform) and automated CI/CD pipeline structures.