Solution Architect-AI Platform

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.

Please send your resume to