AI Transformation Lead
Job Description
Chief Architect – AI Solutions
Experience: 15+ Years
Location - Remote, India
Algoworks
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 seeking a Chief Architect – AI Solutions to design, implement, and scale cutting-edge AI and generative AI systems. This role requires deep expertise in software architecture, system design, and LLM-based AI systems, including Retrieval-Augmented Generation (RAG), embeddings, and prompt engineering. The ideal candidate will lead AI initiatives, collaborate with business and technical stakeholders, and ensure delivery of scalable, reliable, and high-impact AI solutions.
Key Responsibilities
• AI Architecture & System Design
- Lead the design and architecture of AI/ML and generative AI systems, ensuring scalability, reliability, and performance.
- Design LLM-based solutions leveraging RAG, embeddings, and advanced prompt strategies.
- Define best practices for AI/ML model deployment, monitoring, and lifecycle management.
- Collaborate with engineering teams to ensure system design aligns with business and technical requirements.
• Solution Development & Implementation
- Build and oversee the development of APIs, backend systems, and AI pipelines.
- Integrate AI models into enterprise applications, cloud platforms, and production environments.
- Optimize systems for latency, scalability, and computational efficiency.
- Provide technical guidance, articulate complex AI concepts clearly, and align solutions with business objectives.
• Team Leadership & Collaboration
- Lead, mentor, and guide AI engineers and ML specialists in designing and implementing AI solutions.
- Collaborate with cross-functional teams including DevOps, Data Engineering, and Product to ensure smooth delivery.
- Promote adoption of AI architecture standards and best practices across the organization.
• Innovation & Research
- Stay updated on AI/ML trends, generative AI advances, and emerging technologies.
- Evaluate and integrate new AI frameworks, tools, and techniques.
- Drive innovation and continuous improvement in AI architectures and processes.
Required Skills & Qualifications
· Bachelor’s or master’s degree in computer science, Engineering, or a related field.
· 12+ years of experience in software architecture and system design, including at least 3–4 years working with AI/ML or generative AI systems.
· Strong experience with LLM-based systems, including Retrieval-Augmented Generation (RAG), embeddings, and prompt design.
· Hands-on programming experience in Python and building APIs and backend systems.
· Strong understanding of cloud platforms (Azure, AWS, or GCP) and experience building scalable AI systems.
· Strong requirement gathering and stakeholder management skills, including working with non-technical users.
Nice to Have Skills
· Exposure to MLOps frameworks such as MLflow, Kubeflow, or TFX.
· Experience with containerization (Docker/Kubernetes) and cloud-native AI solutions.
· Knowledge of AI model governance, ethics, and bias mitigation strategies.
Desired Attributes
· Strategic thinker with a deep understanding of AI system design and enterprise architecture.
· Strong leadership, mentoring, and decision-making capabilities.
· Analytical, detail-oriented, and proactive in problem-solving.
· Ability to work in a fast-paced, innovative, and collaborative environment.
Interview Process
2 to 3 Rounds of Discussion
