Xcellent Talents
Website:
xcellent-talents.com
Job details:
Role Overview
We are looking for an experienced AI Solutions Architect to lead the design and implementation of scalable AI and Generative AI platforms across enterprise environments.
This role is focused on architecture leadership rather than feature-level engineering. You will define AI solution blueprints, establish engineering standards, evaluate AI technologies, and guide engineering teams in delivering secure, scalable, and cost-efficient AI systems.
You will collaborate closely with executive leadership, product teams, engineering teams, and clients to shape Bosenet’s long-term AI strategy.
Key Responsibilities
AI Architecture & Strategy
- Design and own enterprise AI architecture for GenAI and LLM-powered applications.
- Define standards for multi-agent systems, RAG pipelines, orchestration frameworks, and AI deployment patterns.
- Drive AI platform strategy across cloud-native and hybrid environments.
- Evaluate and recommend build-vs-buy decisions for AI tooling and infrastructure.
Solution Design & Delivery
- Lead architecture workshops and technical discovery sessions.
- Translate business requirements into scalable AI solution blueprints.
- Oversee delivery from architecture design through production deployment.
- Establish reusable AI components and reference architectures.
LLMOps & Governance
- Define governance standards for prompts, evaluations, guardrails, observability, and responsible AI.
- Establish monitoring strategies for hallucination detection, cost tracking, and model performance.
- Drive model versioning, experimentation, and deployment standards.
Cloud & Infrastructure
- Architect AI solutions on AWS, Azure, or GCP.
- Design scalable inference infrastructure, vector databases, and AI pipelines.
- Optimize infrastructure usage, token consumption, and AI operational costs.
Leadership & Collaboration
- Mentor AI engineers and conduct architecture/design reviews.
- Collaborate with Data Science, Platform Engineering, Security, and Product teams.
- Present technical strategies and recommendations to senior stakeholders.
Required Skills & Experience
- 5–8+ years of experience in AI/ML Engineering with at least 2 years in an Architect or Technical Lead role.
- Strong experience designing enterprise AI systems using LLMs and Generative AI.
- Hands-on expertise with:
- RAG Architectures
- Multi-Agent Systems
- Prompt Engineering
- Fine-Tuning Strategies
- AI Orchestration Frameworks
- Strong experience with cloud AI platforms:
- AWS SageMaker / Bedrock
- Azure OpenAI / Azure ML
- GCP Vertex AI
- Experience with AI frameworks and tooling:
- LangChain
- LlamaIndex
- AutoGen
- CrewAI
- Experience with vector databases such as Pinecone, Weaviate, pgvector, or Chroma.
- Strong understanding of Docker, Kubernetes, Terraform, and cloud-native deployment patterns.
- Experience with AI security, governance, compliance, and observability.
- Excellent communication and stakeholder management skills.
Nice-to-Have Skills
- AWS/Azure/GCP Solution Architect Certifications.
- Experience with enterprise AI governance frameworks.
- Experience with real-time inference and streaming AI systems.
- Exposure to OCR, document intelligence, ERP, finance, or workflow automation solutions.
- Experience in client-facing consulting or pre-sales environments.
Core Technology Stack
- Python
- LangChain / LlamaIndex
- OpenAI / Anthropic / Gemini
- AWS Bedrock / SageMaker
- Azure OpenAI / Azure ML
- Vertex AI
- Docker / Kubernetes
- Terraform / IaC
- Vector Databases
- CI/CD Pipelines
- LLMOps & AI Observability
Click on Apply to know more.