Solutions Architect - Applied AI
Solutions Architect - Applied AI
lyzr ai8-10 Years
- Posted 7 hours ago
- Be among the first 10 applicants
Job Description
Location: Bangalore/Hybrid or Remote
Experience: 8 years+
Experience in ML/Advanced NLP: 3-4 years
Experience in LLMs - 1-2 years
Employment Type: Full-Time
About The Role
We are seeking an experienced and innovative AI Solutions Architect to join our team. This role combines deep technical expertise in machine learning, large language models (LLMs), and NLP with consultative skills to help design, guide, and implement cutting-edge AI agents and workflows. You will play a critical role in determining which AI agents should be built, how data should be handled, and how models should be integrated and optimized to deliver intelligent and reliable outcomes.
Key Responsibilities
Core AI/ML Expertise (3–4 years)
Experience: 8 years+
Experience in ML/Advanced NLP: 3-4 years
Experience in LLMs - 1-2 years
Employment Type: Full-Time
About The Role
We are seeking an experienced and innovative AI Solutions Architect to join our team. This role combines deep technical expertise in machine learning, large language models (LLMs), and NLP with consultative skills to help design, guide, and implement cutting-edge AI agents and workflows. You will play a critical role in determining which AI agents should be built, how data should be handled, and how models should be integrated and optimized to deliver intelligent and reliable outcomes.
Key Responsibilities
- Agent Architecture & Workflow Design
- Consult with internal and client teams to determine which agent workflows need to be created for specific use cases.
- Define capabilities, intents, and interaction flows of AI agents to meet business goals.
- Design the system architecture for multi-agent orchestration and model integration.
- Model Strategy & Execution
- Guide the selection, fine-tuning, and integration of LLMs, RAG pipelines, and transformer-based models.
- Define how models will interact with different data modalities (text, audio, video, structured data).
- Evaluate and benchmark model performance and retraining needs.
- Advise on how to configure, enrich, and pre-process data (structured/unstructured) for maximum model performance.
- Oversee entity extraction, topic modeling, summarization, and other NLP-driven enrichment techniques.
- Ensure data pipelines are designed for continuous learning and improvement.
- Lead prototyping and MVP development, translating architecture into production-grade solutions.
- Collaborate with developers to build scalable AI services and interfaces.
- Write clean, efficient, and modular code to integrate AI components.
- Translate complex AI concepts into actionable recommendations for non-technical stakeholders.
- Provide strategic input on product direction, capabilities, and limitations.
- Maintain a high degree of ownership and accountability across all initiatives.
Core AI/ML Expertise (3–4 years)
- Strong background in machine learning and deep learning, including model training and evaluation.
- Experience developing ML-powered enterprise applications.
- Advanced understanding of NLP techniques, including entity extraction, summarization, topic modeling, etc.
- Experience with structured and unstructured data feature engineering.
- Solid understanding of LLM architecture, prompt engineering, and RAG (Retrieval-Augmented Generation) frameworks.
- Exposure to multi-modal agent delivery (text, audio, video).
- Strong problem-solving aptitude applied to real-world use cases.
- Excellent communication and stakeholder management skills.
- Proactive mindset with ownership of end-to-end delivery.
- Experience with cloud-based ML platforms (AWS/GCP/Azure).
- Familiarity with agent orchestration platforms or LangChain-like frameworks.
- Understanding of vector databases, embeddings, and context-aware retrieval systems.
More Info
Job Type:
Industry:
Employment Type:
Key Skills
Feature Engineering
Agent Orchestration Platforms
Context-aware Retrieval Systems
Model Training
Multi-modal Agent Delivery (text
Topic Modeling
LangChain-like Frameworks
Vector Databases
Embeddings
video)
Prompt Engineering
Large Language Models (LLMs)
About Company
Skills:
Sales Engineer, Machine Learning, Data Science, Python, Technical customer-facing roles, Common LLM frameworks and tools, Technical Account Manager, Designing scalable cloud architectures, Integrating with enterprise systems, Solutions Architect