We are seeking an experienced and visionary Solution Architect to join our dynamic
team. As a Solution Architect, you will be the primary technical bridge between our
clients' most complex business challenges and the groundbreaking capabilities of our AI
platform. You will be responsible for designing robust, scalable, and innovative solutions
that leverage our platform's MCP-first architecture to deliver transformative business
value.
This is a key role that requires a blend of deep technical expertise, strategic thinking,
and exceptional client-facing communication skills. You will be instrumental in
demonstrating the power of our platform and ensuring our clients' success.
Key Responsibilities
Client Engagement & Discovery: Collaborate closely with enterprise clients to
understand their business processes, pain points, data ecosystems, and
strategic goals.
Solution Design & Architecture: Design end-to-end solutions by mapping client
requirements to our platform's offerings (e.g., Knowledge Hubs, Conversational
AI, Real-time Insights, and Agentic Automation). Create detailed architecture
documents, data flow diagrams, and technical specifications.
MCP Workflow & Ontology Design: Architect the core intelligence for client
solutions. This includes designing client-specific ontologies and defining the
structure, logic, and composition of Model Context Protocols (MCPs) to automate
complex reasoning and workflows.
Technical Leadership: Serve as the deep technical expert on the platform for
both clients and internal teams. Provide guidance on best practices for data
integration, RAG implementation, and agentic automation.
Proof of Concept & Prototyping: Lead the technical design and development of
Proof of Concept (PoC) projects to demonstrate the feasibility and value of our
solutions for specific client use cases.
Cross-functional Collaboration: Work closely with our Engineering teams to
ensure proposed solutions are feasible, scalable, and align with the platform's
core architectural principles. Partner with the Product team to provide feedback
from the field that informs the future roadmap.
Implementation & UAT Guidance: Provide architectural oversight and technical
guidance during the implementation and User Acceptance Testing (UAT) phases
of client projects, ensuring the delivered solution meets the design specifications
and business requirements.
Continuous Learning: Maintain a deep understanding of the rapidly evolving AI
landscape, including new LLM capabilities, agentic frameworks, and industry
best practices, and integrate this knowledge into solution designs.
Required Qualifications & Skills
Experience: 8+ years of experience in a technical role such as Solution
Architecture, Enterprise Architecture, or senior-level Software Engineering, with
at least 3+ years in a client-facing capacity.
Architectural Expertise: Proven ability to design and document complex,
distributed, and scalable software systems. Deep understanding of
microservices, event-driven architecture, and MCP-first design principles.
AI/ML Acumen: Strong foundational knowledge of modern AI concepts, including
Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and
vector databases (e.g., Qdrant, Pinecone, Weaviate).
Data Integration: Hands-on experience designing data pipelines and integrating
with diverse enterprise data sources (e.g., relational databases like PostgreSQL,
unstructured document stores like SharePoint, APIs, and data warehouses).
Cloud Proficiency: Experience architecting solutions on a major cloud platform
(AWS, Azure, or GCP).
Technical Foundation: Proficiency in Python is strongly preferred. Familiarity with
containerization (Docker) and orchestration (Kubernetes) is essential.
Communication: Exceptional verbal and written communication skills, with the
ability to explain complex technical concepts to both technical and non-technical
audiences.
Preferred Qualifications (Nice to Have)
Direct, hands-on experience designing or building systems using agentic AI
frameworks (e.g. LangGraph, CrewAI).
Knowledge of semantic web technologies, including ontologies (OWL/RDF) and
graph databases (e.g., Neo4j).
Familiarity with the concepts behind the Model Context Protocol (MCP) or similar
advanced agentic architectures.
Experience with modern observability stacks, particularly OpenTelemetry.
Experience designing multi-tenant enterprise software platforms.
Knowledge of enterprise security patterns and identity management systems.