Role: Principal Solution Architect - AI
Location: India, remote
Experience: 10 Years
Algoworks
www.algoworks.com
About the company
Algoworks is an award-winning artificial intelligence, engineering services and experience transformation firm with offices across the United States, Europe, South America and India. We bring together a global team of engineers, architects, designers, researchers and operators united by rigor, accountability and a commitment to delivering measurable results.
For over 20 years, Algoworks has partnered with Fortune 500 organizations across the Americas, Europe and Asia to define, build and run technology that drives meaningful business outcomes. Our work combines human-centered design, engineering excellence and AI-powered capabilities to solve complex challenges with clarity and precision. Innovation, particularly in the responsible application of AI, is embedded in how teams approach problem-solving and continuous improvement.
At Algoworks, growth is continuous and closely tied to impact. Teams collaborate across geographies and disciplines, strengthening outcomes through shared insight and collective expertise. The culture values transparency, open dialogue and an environment where every voice is heard and contribution is recognized.
Through collaboration, accountability and a focus on results, Algoworks operates at the intersection of technology and people, building not only advanced systems but strong global teams that elevate performance and create lasting impact.
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Role overview
We are looking for an AI Solution Architect who can design and build practical AI systems on top of enterprise data and business workflows.
This is not a research role. This is a hands-on role focused on solving real business problems using AI.
The person will work closely with cross-functional teams to understand how work happens and translate that into AI-enabled solutions.
Key focus areas include document intelligence, knowledge-driven systems, and AI-powered search, insights, and content generation across enterprise platforms.
Key responsibilities:
1. Understand the business and gather requirements
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Work directly with stakeholders across functions (Sales, Delivery, Finance, HR).
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Understand real workflows and how information flows across systems.
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Identify where AI can reduce effort, improve quality, or automate decisions.
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Convert loosely defined problems into clear, buildable requirements.
2. Design and build AI systems
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Design end-to-end AI systems on top of enterprise data and documents.
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Build pipelines for:
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Document ingestion
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Classification
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Information extraction
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Relationship mapping
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Develop systems for intelligent search, Q&A, and content generation.
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Enable AI-driven workflows that assist users in creating and refining structured outputs.
3. Work with enterprise systems
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Integrate AI solutions with document repositories and enterprise platforms.
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Work with APIs and middleware to connect AI systems with business tools.
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Ensure outputs are usable within existing workflows, not separate systems.
4. Build fast, then improve
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Deliver working solutions quickly, even if not perfect.
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Iterate based on real user feedback.
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Make practical trade-offs between speed, accuracy, and scalability.
5. Own UX / UI simplicity
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Design simple, intuitive user flows.
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Ensure users can easily:
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Provide inputs
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Review outputs
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Interact with AI systems
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Work with frontend teams or directly build lightweight interfaces when needed.
6. Drive architecture and standards
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Define architecture for AI pipelines (LLMs, vector stores, knowledge graphs).
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Ensure systems are scalable, secure, and maintainable.
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Architect multi-cloud or hybrid cloud AI solutions, leveraging services from AWS, Azure, or GCP for scalable compute, storage, orchestration, and deployment.
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Ensure seamless integration of ML/AI systems via RESTful APIs with frontend interfaces (e.g., dashboards, portals) and backend systems (e.g., CRMs, ERPs).
Qualifications required:
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Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
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8–12 years of experience in software architecture and system design, including at least 3–4 years working with AI/ML or generative AI systems.
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Strong experience with LLM-based systems, including Retrieval-Augmented Generation (RAG), embeddings, and prompt design.
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Strong hands-on programming skills (preferably Python) and experience building APIs and backend systems.
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Strong understanding of cloud platforms (Azure, AWS, or GCP) and building scalable AI systems.
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Strong requirement gathering and stakeholder management skills, with the ability to work with non-technical users.
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Strong requirement gathering and stakeholder management skills, with the ability to work with non-technical users.
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Clear written communication and documentation skills.
Nice to have skills:
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Experience with document intelligence, vector databases, knowledge graphs, or AI-powered search systems.
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Exposure to frontend/UI design for AI workflows.
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Multi-cloud or hybrid cloud architecture experience.
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Familiarity with enterprise platforms, integrations, and business automation systems.
Must have skills:
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8–12 years of experience in software architecture, system design, and enterprise solution development.
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Strong hands-on experience with AI/ML systems, LLMs, RAG, embeddings, and enterprise AI workflows.
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Expertise in Python, API development, cloud platforms (AWS/Azure/GCP), and scalable AI architecture.
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Strong stakeholder management, requirement gathering, and business process understanding.
Desired attributes:
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Highly curious and proactive: constantly exploring new AI tools and technologies.
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Interested in understanding how systems and processes work
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Structured thinker who approaches problems rigorously
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Enjoys experimentation and rapid testing of new technologies
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Able to connect engineering work to measurable business outcomes
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Strong listener and interviewer: able to ask the right questions and uncover insights from teams.
Interview process
2 rounds of discussion.
