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Principal Technical Architect

3 months, 2 weeks ago
India
Full-time
Lead
Software Architect
Software Development
AWS Azure DynamoDB GCP JSON Kafka Microservices Neo4j NetSuite OAuth Phoenix Python REST API Salesforce SAP SOAP XML
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Workato

Workato

Workato is the Enterprise Automation Platform that enables seamless integration and automation of workflows for both business and IT teams, utilizing AI-powered technology for efficient outcomes.

IT Services
251-1K
Founded 2013
$415M raised
View All Jobs 8

Description

  • Serve as an expert AI architect in enterprise pre-sales and post-sales engagements, including roadmap planning and technical deep dives.
  • Lead architecture workshops with customers to define AI automation strategy, agent design, integration patterns, and governance frameworks.
  • Advise customers on prompt engineering, agent orchestration, evaluation methods, confidence calibration, human-in-the-loop design, and continuous learning loops.
  • Build reusable technical assets such as reference architectures, solution blueprints, demo environments, and best-practice documentation.
  • Create technical collateral including white papers, webinars, blog posts, and conference talks to support Workato’s thought leadership.
  • Partner with Product and Engineering to translate field feedback into platform roadmap improvements.
  • Support strategic accounts across the US, EMEA, and APAC, with up to 20% global travel as needed.
  • Architect and implement core subsystems of the autonomous Customer Success agent platform, including memory layers, orchestration, and decision trace architecture.
  • Design and build a Customer Knowledge Graph to model customer context, policies, decisions, and operational artifacts for governance and traceability.
  • Implement confidence-based autonomy frameworks, escalation routing, and evaluation metrics for decision quality and learning velocity.

Requirements

  • B.Tech/BE or higher in Computer Science, Engineering, or a related field.
  • 15+ years of total relevant experience in enterprise software architecture, design, and implementation.
  • 8+ years of hands-on experience with integration platforms such as MuleSoft, TIBCO, Oracle SOA, webMethods, or similar.
  • 2+ years of applied AI/agents engineering experience building systems with LLMs and agent frameworks in production.
  • Hands-on experience designing AI agent systems, including multi-step reasoning, tool-use orchestration, and autonomous execution frameworks.
  • Working knowledge of Python agent frameworks such as LangGraph, Claude Agent SDK, or equivalent; LangGraph with persisted state and human-in-the-loop patterns is strongly preferred.
  • Experience with graph database design and implementation, including entity modeling, relationship extraction, graph querying, and contextual retrieval; Neo4j or NetworkX experience is a plus.
  • Practical experience with RAG architectures, vector databases, embedding strategies, and hybrid retrieval.
  • Experience building evaluations and testing for AI systems, including confidence calibration, A/B testing, and regression testing.
  • Familiarity with production-scale prompt engineering, including structured prompting, output parsing, retry/fallback strategies, and prompt versioning.
  • Experience with LLM observability tools such as Langfuse, LangSmith, Phoenix, or similar.
  • Experience with MCP (Model Context Protocol) standards for LLM-to-system integration.
  • Strong expertise in enterprise integration patterns, APIs, cloud platforms, enterprise applications, and security/governance requirements.
  • Background in customer success platforms or CRM architecture is preferred.
  • Prior experience in a customer-facing technical role at a SaaS or platform company is preferred.
  • Contributions to open-source AI/agent projects or published technical content in applied AI are preferred.
  • Ability to communicate complex AI and architecture concepts to both technical teams and executive stakeholders.
  • Strong consultative problem-solving ability and comfort operating in ambiguity.
  • Collaborative working style across Product, Engineering, Customer Success, Sales, and Marketing.
  • Excellent written communication for architecture documents, white papers, and technical briefs.
  • Ability to stay current with the rapidly evolving AI agent ecosystem and translate emerging patterns into practical guidance.

Benefits

  • Flexible, trust-oriented culture with strong ownership of individual roles.
  • Support for balancing productivity with self-care.
  • Vibrant and dynamic work environment.
  • Benefits available to support employees inside and outside of work.
  • Recognized as the #1 best company for remote workers by Quartz.

Interested in this position?

Apply directly on the company website

Apply Now

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