Associate Principal Engineer, AI Architect

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Associate Principal Engineer, AI Architect based in India.

This senior architecture role offers the opportunity to shape the design and delivery of enterprise-grade AI solutions at scale. You will translate complex and often ambiguous business challenges into durable technical architectures spanning AI, backend, frontend, and cloud infrastructure. The role focuses heavily on Generative AI, Agentic AI, LLMs, RAG, and intelligent user-facing applications. You will influence technical strategy across teams while establishing engineering standards for security, scalability, performance, and responsible AI. Working closely with product, design, data, business, and technical leaders, you will turn emerging AI capabilities into practical, production-ready solutions. The environment is highly collaborative and fast-moving, with opportunities to mentor engineers, lead technical discovery, and drive innovation across multiple initiatives.

Accountabilities:

• Translate client business objectives, functional requirements, and technical constraints into scalable, secure, and sustainable AI architectures.
• Own the technical vision and architecture for AI-powered applications using technologies such as Python, React, Generative AI, and modern cloud platforms.
• Design scalable backend platforms supporting LLM inference, RAG pipelines, agent orchestration, APIs, and microservices.
• Architect AI-native frontend experiences, including conversational interfaces, copilots, intelligent dashboards, and other user-facing applications.
• Lead the design and implementation of complex GenAI workflows combining LLMs, tools, APIs, structured data, and user context.
• Drive AI platformization through reusable components, SDKs, frameworks, and engineering patterns that can be adopted across teams and products.
• Establish standards and best practices for prompt engineering, model integration, evaluation, observability, AI-assisted development, and production quality.
• Define and review non-functional requirements and architecture considerations covering scalability, extensibility, security, performance, reliability, and user experience.
• Ensure enterprise readiness through appropriate security, privacy, compliance, AI governance, and Responsible AI practices.
• Evaluate alternative technical approaches and identify solutions that best address client requirements, including conducting proofs of concept where appropriate.
• Review architecture, design documents, and critical codebases, helping teams resolve complex technical challenges and maintain high engineering standards.
• Lead technical discovery, solutioning, and client or executive-facing workshops for high-impact initiatives.
• Partner with product managers, designers, data teams, business leaders, and engineers to translate strategic objectives into executable technical strategies.
• Mentor engineers, support agile delivery practices, and communicate complex architectural and AI concepts clearly to technical and non-technical stakeholders.
• Investigate production and development issues systematically, identify root causes, and clearly document and justify architectural and technical decisions.

Requirements:

• 9+ years of overall professional experience in software engineering, architecture, or a closely related technical discipline.
• Bachelor’s or master’s degree in Computer Science, Information Technology, or a related field.
• Strong software engineering expertise with significant hands-on depth in Python.
• Proven experience developing microservices and APIs using technologies such as Python, FastAPI, and Node.js, particularly for integrating AI and deep learning models into enterprise applications.
• Demonstrated experience architecting and delivering production-grade Generative AI applications at scale.
• Strong system-design capabilities across backend, frontend, AI infrastructure, and distributed systems.
• Hands-on expertise designing ML, Generative AI, and Agentic AI solutions involving LLMs, RAG, autonomous agents, and AI orchestration.
• Strong Enterprise Architecture and Solution Design experience, with the ability to convert ambiguous business problems into durable technical solutions.
• Experience building end-to-end AI pipelines and integrating vector databases such as Pinecone, Weaviate, or Milvus.
• Practical experience deploying secure, production-grade AI solutions across AWS, Azure, and/or GCP, including hybrid and multi-cloud environments.
• Strong understanding of CI/CD, access control, scalable compute, AI-assisted development, and cloud-native engineering practices.
• Knowledge of AI Governance, Responsible AI, AgentOps/GenAIOps, Knowledge Graphs, and Semantic Layer Architecture.
• Experience defining technical strategies, influencing architecture across teams or pods, and establishing engineering standards.
• Strong analytical and critical-thinking abilities, with a structured approach to evaluating architecture alternatives and technical trade-offs.
• Excellent communication and stakeholder-management skills, including the ability to influence senior technical and business leaders.
• Ability to mentor engineers, collaborate effectively in agile environments, and use tools such as Jira to support delivery workflows.
• Strong technical documentation skills and the ability to explain complex AI and architecture concepts to non-technical audiences.

Benefits:

• Competitive compensation aligned with the seniority and scope of the role.
• Opportunity to work on large-scale enterprise AI and Generative AI initiatives.
• Exposure to advanced technologies including LLMs, RAG, Agentic AI, AI platforms, vector databases, and cloud architectures.
• Opportunities to influence technical strategy and architecture across multiple teams and products.
• Collaborative environment with cross-functional interaction across engineering, product, design, data, and business teams.
• Opportunities to mentor technical talent and contribute to engineering standards and best practices.
• Exposure to emerging AI research and opportunities to apply new technologies to real-world enterprise challenges.
• Professional growth through complex technical projects, client engagements, and architecture leadership responsibilities.
• Opportunity to work with modern cloud, AI, distributed-system, and AI-assisted development technologies.