C5i - Solution Architect

Description :

Responsibilities :

- Design and own full-stack solution architectures (frontend, backend, APIs, databases, cloud) for enterprise applications.

- Define and enforce architectural standards, coding practices, and integration patterns.

- Lead technical design sessions and guide development teams through implementation.

- Architect and integrate agentic systems (e. g., autonomous agents, multi-agent orchestration) into full-stack applications.

- Collaborate with AI/ML teams to embed intelligent features using LLMs, RAG pipelines, and cognitive services.

- Evaluate and implement frameworks like LangChain, Semantic Kernel, or AutoGPT for agentic workflows.

- Provide technical mentorship to developers and engineers across the stack.

- Conduct code and architecture reviews to ensure performance, scalability, and security.

- Stay ahead of emerging trends in AI, agentic systems, and full-stack development.

- Present architectural decisions and trade-offs to leadership and clients.

- Collaborate with business and technical stakeholders to identify AI use cases and translate them into scalable architectures.

- Evaluate and select appropriate AI tools, frameworks, and cloud services (e. g., Azure OpenAI, AWS Bedrock, Vertex AI, Hugging Face, LangChain, CrewAI, n8n).

- Implement AI orchestration and agent-based workflows using tools such as CrewAI, LangChain, Model Context Protocol (MCP), or custom microservice architectures.

- Define and oversee data and model pipelines, including governance, MLOps, and observability.

- Work closely with product managers, business analysts, and UX designers to align technical solutions with business goals.

- Partner with data engineers, ML engineers, and developers to build production-grade AI APIs, agents, and automation workflows.

- Integrate AI capabilities into enterprise systems (CRM, ERP, data platforms, and custom applications).

- Ensure compliance with ethical AI, responsible AI, and data privacy standards.

- Develop architectural blueprints, PoCs, and reference implementations to accelerate adoption.

Requirements :

- Bachelor's or master's degree in computer science, Engineering, or related field.

- 6-7 years of experience in full-stack development and solution architecture.

- 2+ years of experience with AI and agentic technologies : LLMs (OpenAI, Azure OpenAI, etc. ), Agentic frameworks (LangChain, Semantic Kernel, etc. ), ML model integration and orchestration.

- Experience with microservices, RESTful APIs, and event-driven architectures.

- Knowledge of DevOps practices and CI/CD pipelines.

- Strong understanding of LLM architecture, prompt engineering, RAG (Retrieval-Augmented Generation), and vector databases (e. g., Pinecone, FAISS, Chroma, Weaviate).

- Familiarity with AI orchestration frameworks and workflow automation tools (e. g., LangChain, CrewAI, n8n, MCP).

- Solid grounding in data architecture, API design, and cloud platforms (AWS, Azure, GCP).

- Knowledge of ML frameworks (TensorFlow, PyTorch, Scikit-learn) and GenAI SDKs (OpenAI, Anthropic, LlamaIndex).

- Demonstrated ability to design and integrate AI components within enterprise applications and cloud-native architectures.

- Strong communication skills, capable of engaging both technical and non-technical stakeholders.

- Proficiency in modern full-stack technologies :

1. Frontend : React, Angular, or Vue.js .

2. Backend : Node.js, . NET Core, Python (FastAPI, Flask).

3. Databases : SQL, NoSQL (MongoDB, Cosmos DB).

4. Cloud : Azure, AWS, or GCP.

Preferred Qualifications/Nice to have :

- Experience with MLOps / AIOps platforms (MLflow, Kubeflow, SageMaker, Vertex AI Pipelines).

- Exposure to multi-modal AI (text, image, speech).

- Certifications in cloud architecture or AI/ML (Azure AI Engineer, AWS ML Specialty, GCP AI Engineer).

- Contributions to AI research, open-source projects, or technical communities.