8 hours ago
Bengaluru, IndiaStaff+
Responsibilities
- Own the target architecture and multi-year technical evolution for complex enterprise products and programs.
- Lead architectural decisions from problem framing through implementation, including trade-offs, architecture decision records, technical risks, and outcome validation.
- Define and govern production AI architecture for generative AI, LLM workflows, agentic patterns, RAG, model lifecycle, evaluation, observability, safety, privacy, and responsible AI.
- Translate business strategy into platform capabilities, architecture roadmaps, sequencing decisions, investment choices, and measurable technical outcomes.
- Align multiple engineering and product teams around principles, reference patterns, interfaces, and quality attributes.
- Represent architecture decisions in cross-functional governance and executive forums and drive decisions to closure.
- Use prototypes, benchmarks, threat models, cost models, reliability data, and operational evidence to validate recommendations.
- Guide modernization toward cloud-native, API-first, event-driven, and AI-ready architectures.
- Establish architecture governance, design reviews, technical standards, exception management, and conformance reviews.
- Influence secure design, automated testing, platform engineering, observability, performance engineering, disaster recovery, CI/CD, and production readiness practices.
- Mentor senior engineers, lead engineers, and architects and improve technical reasoning, documentation, communication, and ownership.
- Review critical designs and code, build proofs of concept, investigate high-impact technical issues, and participate in complex problem solving.
Requirements
- 16+ years of software engineering experience, including substantial architecture leadership for large-scale enterprise products, platforms, or multi-team programs.
- Demonstrated accountability for consequential architectural decisions with broad product, customer, operational, or organizational impact.
- Deep expertise in Java and modern backend architecture, including Spring, microservices, and asynchronous integration patterns; C/C++ experience is valuable.
- Applied experience delivering production capabilities using LLMs, generative AI, machine learning, or intelligent automation.
- Practical knowledge of model selection, prompting, grounding, evaluation, guardrails, latency, cost, and lifecycle operations.
- Experience with PyTorch, Hugging Face, commercial model APIs, vector databases, embeddings, model gateways, and LLMOps practices.
- Expertise in distributed systems, domain-driven design, event-driven architecture, data architecture, messaging, concurrency, caching, persistence, and fault-tolerant design.
- Experience designing for enterprise security, privacy, compliance, multi-tenancy, scalability, availability, disaster recovery, observability, performance, and cost efficiency.
- Advanced experience with at least one major cloud platform such as AWS, Azure, or GCP, plus containers, Kubernetes, infrastructure automation, CI/CD, and platform engineering.
- Ability to lead through influence across organizational boundaries and establish credibility with senior technical and business stakeholders.
- Exceptional written, verbal, and visual communication skills, including executive communication and explanation of complex trade-offs.
- Experience architecting AI-enabled products in regulated, high-volume, B2B, integration, or mission-critical environments is valued.
- Experience with agentic systems, RAG architectures, knowledge graphs, semantic search, AI-assisted automation, or predictive analytics is valued.
- Experience establishing architecture reviews, technology standards, reference architectures, or platform strategies is valued.
- Background in performance engineering, threat modeling, data governance, FinOps, SRE, or large-scale modernization is valued.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent advanced professional experience.
Categories
About OpenText
OpenText builds enterprise information management software and cloud services spanning content services, customer communications, B2B/EDI integration, eDiscovery, and cybersecurity. It sells licenses, subscriptions, and managed services to large enterprises and governments, with offerings available on-premises and in the cloud. Founded in 1991 and headquartered in Waterloo, Ontario, OpenText (NASDAQ/TSX: OTEX) has expanded through major acquisitions, including Micro Focus (2023) and Documentum (2017).