About Company:

We are a global leader in maritime solutions, with significant focus on digital transformation across the industry. Our mission is to redefine our fleet operations through intelligent platforms, IoT ecosystems, AI and scalable cloud architectures. By combining deep domain expertise with cutting-edge technology, we enable safer, smarter, and more sustainable maritime operations worldwide.

About the Role:

We are looking for a seasoned Sr. Solution Architect who combines the rigor of Enterprise system design with deep expertise in AI Platforms and Agentic AI. In this role, you will define the architectural vision for our core systems while leading the design of next-generation autonomous agent frameworks. You will bridge the gap between traditional software architecture (scalability, security, reliability) and the probabilistic nature of Large Language Models (LLMs).

Key Responsibilities:

1. Enterprise & System Architecture :

- System Design: Design robust, scalable, and secure end-to-end architectures for complex distributed systems, ensuring high availability and fault tolerance.

- Integration Strategy: Define patterns for integrating AI capabilities into existing enterprise workflows, legacy systems, and microservices architectures.

- Technical Governance: Establish architectural standards, code quality guidelines across engineering teams.

- Stakeholder Management: Translate business requirements into technical specifications and communicate architectural decisions to C-level executives and product leaders.

2. AI Platform & Agentic AI:

- Agentic Frameworks: Architect Multi-Agent Systems where specialized agents (Planning, Execution, Research) collaborate to solve complex workflows.

- LLM Orchestration: Design the inference layer for managing multiple LLM providers (OpenAI, Anthropic, Gemini, local models), implementing fallback strategies, caching, and cost optimization.

- Memory & Context: Architect advanced context management systems, including Vector Databases (RAG) and shared memory structures for long running agent sessions.

- Tooling Ecosystem: Design secure protocols for agents to interface with external tools (File systems, Browsers, APIs) via standards like Model Context Protocol (MCP).

Required Qualifications:

1. Core Architecture Skills:

- Experience: 10+ years in software engineering with 5+ years as a Solution Architect.

- Cloud Native: Expert knowledge of cloud platforms (AWS, Azure, or GCP), containerization (Kubernetes/Docker), and serverless patterns.

- Backend Engineering: Deep proficiency in TypeScript/Node.js or Python, with strong experience in API design (REST, GraphQL, WebSockets).

- Data Architecture: Experience designing complex data models using both Relational (PostgreSQL, SQLite) and NoSQL databases.

2. AI & Agentic Skills:

- Agentic AI: Proven understanding of agent architectures (ReAct, Plan-and-Solve), tool calling, and multi-agent orchestration patterns.

- AI Infrastructure: Experience building or architecting platforms that leverage LLMs, Embeddings, and Vector Stores (Pinecone, Weaviate, Milvus).

- MLOps: Familiarity with the lifecycle of deploying and monitoring AI models in production.

Preferred Qualifications:

- Hands-on experience with LangChain, AutoGPT, or custom agent frameworks.

- Knowledge of local-first architectures and embedded databases (SQLite).

- Certifications: AWS Certified Solutions Architect (Professional) or similar.