AI System Architect

Engineer V – AI Architecture | Agentic AI & Conversational AI

Location: Gurugram, India | Work Model: Hybrid | Level: Engineer V

About Anaplan

Anaplan is a leading enterprise planning and decision-making platform that enables organizations to connect strategy, planning and execution across finance, supply chain, workforce and other critical business functions. As enterprises increasingly move toward AI-powered decision-making, Anaplan is building the next generation of intelligent experiences that combine enterprise data, advanced analytics, Generative AI and automation.

We are looking for an exceptional Engineer V – AI Architecture to play a pivotal role in defining and building this future.

About the Role

The Engineer V – AI Architecture is a senior technical architecture role focused on the design and evolution of Anaplan’s next generation of Agentic AI and Conversational AI capabilities. The role sits at the intersection of AI, software architecture, distributed systems and enterprise product engineering and is intended for an architect who is equally comfortable discussing system architecture at a strategic level and getting hands-on with the technology when required.

You will define how intelligent agents interact with users, enterprise data, business applications, APIs and planning capabilities. You will architect systems that can understand natural-language intent, maintain context, reason over relevant information, retrieve enterprise knowledge, invoke tools, orchestrate multi-step workflows and deliver reliable outcomes.

This is not an architecture-only position. We are looking for someone who still enjoys engineering and is comfortable moving from architecture diagrams and technical strategy to prototypes, experiments and production-quality code. While architecture and technical leadership will be the primary focus, hands-on coding will be an important part of the role when required to validate architectural decisions, develop reference implementations, build critical capabilities or solve complex technical problems. Depending on business and project requirements, approximately 20–30% of the role may involve hands-on engineering and coding.

What You Will Work On

You will be responsible for shaping the technical architecture of AI-powered experiences across the Anaplan platform. This includes designing intelligent agent architectures capable of understanding business intent and context, determining the appropriate actions or information required, interacting with enterprise systems and executing workflows in a secure and controlled manner.

You will help evolve Anaplan from traditional conversational experiences toward sophisticated agentic systems that can reason, plan, retrieve information, use enterprise tools and collaborate across multiple services. You will establish architectural patterns for agent orchestration, state and memory management, tool and function calling, context management, retrieval, workflow execution and human-in-the-loop controls.

A significant part of the role will involve designing Conversational AI architecture that allows users to interact naturally with complex planning and decision-making capabilities. You will think deeply about multi-turn conversations, context preservation, intent understanding, response generation, grounding, explainability and the boundary between deterministic business logic and probabilistic AI.

You will also architect Retrieval-Augmented Generation solutions that enable AI systems to work effectively with enterprise knowledge and data. This will require strong understanding of embeddings, semantic and hybrid retrieval, vector search, metadata, ranking, context construction, authorization-aware retrieval and techniques for improving grounding and reducing hallucinations.

You will evaluate and apply modern foundation models and AI technologies based on business requirements rather than simply adopting the latest technology. You will consider model capability, reasoning quality, latency, cost, context windows, reliability, structured outputs, tool calling and model routing, and determine where approaches such as prompting, RAG, fine-tuning, conventional software or agentic workflows are most appropriate.

Hands-on Engineering

Although the role is architecturally oriented, you will remain technically close to the implementation. You may write code in Python, Java, C#, Go or other relevant technologies to build prototypes, validate architecture, develop AI workflows, implement critical components or demonstrate technical feasibility.

You will be expected to understand implementation details deeply enough to challenge designs, identify technical risks and make informed architectural decisions. The strongest candidate will be someone who can move naturally between designing a distributed AI platform, reviewing an architecture document, experimenting with an LLM-based workflow and writing the code required to prove that the approach works.

You will work closely with engineering teams to ensure that architecture does not remain theoretical. You will help translate architectural concepts into scalable, maintainable and production-ready software and will remain engaged through implementation, performance optimization and operationalization.

Enterprise AI Architecture

The systems you design will need to operate within the realities of enterprise software. You will therefore consider scalability, availability, resilience, observability, security, privacy, governance, performance and cost as first-class architectural concerns.

You will design AI capabilities that integrate with microservices, APIs, event-driven systems, enterprise data platforms and cloud infrastructure. You will work across service boundaries and help establish patterns for asynchronous processing, orchestration, caching, fault tolerance, high availability and graceful failure.

You will also help establish the architectural foundations required to make AI systems measurable and trustworthy. This includes approaches for evaluating response quality, groundedness, hallucination, retrieval performance, agent success, tool selection, latency, token consumption and overall task completion.

Security and Responsible AI

Enterprise AI introduces unique security and governance challenges, and you will be expected to incorporate these considerations directly into the architecture. You will work with security and platform teams to address concerns such as data privacy, identity and authorization, secure retrieval, prompt injection, data leakage, agent permissions, tool access, auditability and protection of sensitive enterprise information.

The architecture should enable AI systems to be powerful without becoming uncontrolled. You will help establish appropriate guardrails, authorization boundaries, monitoring and human-approval mechanisms for agent-driven actions.

Technical Leadership

At Engineer V level, you will operate as a senior technical authority and architectural leader. You will influence engineering teams through strong technical judgment, design thinking and hands-on credibility.

You will work closely with Product, Engineering, AI/ML, Data, Security, Platform and UX teams to translate complex business requirements into technically sound solutions. You will lead architecture discussions, drive important technical decisions, establish reusable design patterns and influence the long-term AI technology roadmap.

You will also mentor senior engineers and architects, raise engineering standards and help create a culture where AI solutions are designed with the same rigor expected of mission-critical enterprise software.

What We Are Looking For

We are looking for an experienced software architect or senior engineer with 12+ years of experience designing and building sophisticated software systems, with substantial exposure to distributed systems, cloud architecture and modern AI technologies.

You should have meaningful hands-on experience with Generative AI, Large Language Models, Agentic AI, Conversational AI or closely related technologies, ideally having taken AI-powered solutions from experimentation or proof of concept through production.

Strong software engineering fundamentals are essential. You should be highly comfortable with at least one modern programming language and have substantial experience designing APIs, microservices, cloud-native applications and distributed systems.

You should have a deep understanding of modern LLM application architecture, including RAG, embeddings, vector search, prompting, context management, tool and function calling, agent orchestration and AI evaluation. Experience with technologies such as Semantic Kernel, LangChain, LangGraph, OpenAI, Azure OpenAI, Anthropic, Google Gemini, Azure AI Search, vector databases or comparable technologies would be valuable.

Experience with multi-agent systems, MCP, AI observability, LLM evaluation, enterprise knowledge systems and secure AI architectures would be particularly relevant.

Most importantly, you should be able to demonstrate that you understand the difference between building an AI demo and engineering an enterprise-grade AI system.

The Ideal Candidate

The ideal candidate is an architect who is deeply technical, commercially pragmatic and genuinely hands-on. You understand that successful AI architecture is not simply about selecting an LLM or implementing a chatbot. It requires thoughtful integration of models, data, software systems, business logic, security, infrastructure and user experience.

You are comfortable asking difficult architectural questions, challenging assumptions and making trade-offs between intelligence, reliability, latency, scalability and cost. You can communicate a complex architecture to senior leadership and then sit with engineers to work through the implementation details.

You are curious about emerging AI technologies but grounded in strong software engineering principles. You know when to use an agent and when a deterministic workflow is better. You understand where LLMs add value and where conventional software should remain in control.

Most importantly, you want to help build AI systems that move beyond simple conversational interfaces and become trusted, intelligent and deeply integrated into enterprise decision-making.

Why This Role

This is an opportunity to shape the architecture of AI at one of the world's leading enterprise planning platforms. You will have the opportunity to work on problems at the intersection of Agentic AI, Generative AI, enterprise software, decision intelligence and large-scale distributed systems.

Your architecture will influence how users interact with Anaplan, how intelligent agents reason over enterprise information, how AI interacts with business processes and ultimately how organizations use AI to make better planning and business decisions.

If you are a Technical Architect who still loves to code, an AI engineer who thinks in systems, and a technology leader who wants to define what enterprise Agentic AI looks like at scale, this is an opportunity to make a significant impact at Anaplan.