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
1. 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.
2. 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).
3. 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.
4. 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.

Work arrangement
Hybrid